Blame for programs/layer06/21/L06_F21900-21999.py

"""GPT-2 SAE last-token programs, layer 6 -- features 21900 to 21999 (100 programs).

One function per SAE feature. Grouped 100 to a file so the set stays browsable;
the programs themselves are unchanged.
"""

def prog_L06F21900(input_tokens):
    """4 token families, 10 surface forms (train F1 of the uncapped optimum: 0.656).
    Fires at 22,854 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: instructions for utilizing various tools or techniques"""
    # --- end external annotation ---
    fire = {
        # use  (13,415 firings)
        ' use', ' uses', ' Use', 'Use', ' Uses', ' USE', ' Useful',
        # utilize  (109 firings)
        ' utilize',
        # employ  (102 firings)
        ' employ',
        # usable  (87 firings)
        ' usable',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'use-family', 1

def prog_L06F21901(input_tokens):
    """12 token families, 12 surface forms (train F1 of the uncapped optimum: 0.207).
    Fires at 13,088 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to a specific entity or organization"""
    # --- end external annotation ---
    fire = {
        # c  (2,311 firings)
        'C',
        # columbia  (355 firings)
        ' Columbia',
        # #  (134 firings)
        '#',
        # budget  (126 firings)
        ' Budget',
        # ul  (95 firings)
        'UL',
        # ali  (80 firings)
        'ali',
        # oca  (67 firings)
        'oca',
        # band  (52 firings)
        'band',
        # pay  (50 firings)
        'payer',
        # ibi  (43 firings)
        'ibi',
        # aca  (40 firings)
        'aca',
        # uru  (36 firings)
        'uru',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'c-family', 1

def prog_L06F21902(input_tokens):
    """19 token families, 19 surface forms (train F1 of the uncapped optimum: 0.156).
    Fires at 23,500 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: variations of the prefix "und" in words"""
    # --- end external annotation ---
    fire = {
        # en  (674 firings)
        'en',
        # of  (547 firings)
        'of',
        # ig  (499 firings)
        'ig',
        # ul  (225 firings)
        'ul',
        # ew  (177 firings)
        'ew',
        # et  (176 firings)
        'ET',
        # é  (156 firings)
        'é',
        # ro  (148 firings)
        'RO',
        # ian  (143 firings)
        'IAN',
        # ere  (118 firings)
        'ere',
        # ef  (111 firings)
        'ef',
        # pre  (85 firings)
        'pre',
        # der  (82 firings)
        ' der',
        # des  (74 firings)
        'des',
        # eter  (74 firings)
        'eter',
        # ieg  (65 firings)
        'ieg',
        # esc  (63 firings)
        'esc',
        # erm  (61 firings)
        'erm',
        # ener  (60 firings)
        'ener',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'en-family', 1

def prog_L06F21903(input_tokens):
    """17 token families, 17 surface forms (train F1 of the uncapped optimum: 0.106).
    Fires at 163,372 of 36,786,566 positions.
    Fires at 0.44% of positions, and
    token rules do not serve features this dense: median test F1 0.086
    across the 37,173 features above 0.39% of positions, against 0.763 for
    the 76,283 below 0.016%. Read this fire set as the best available
    approximation, not as what the feature does."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: occurrences of specific days and actions related to meetings or interactions"""
    # --- end external annotation ---
    fire = {
        # on  (13,252 firings)
        ' on',
        # at  (8,344 firings)
        ' at',
        # aft  (4,477 firings)
        ' after',
        # dur  (2,461 firings)
        ' during',
        # before  (1,474 firings)
        ' before',
        # since  (1,037 firings)
        ' since',
        # while  (995 firings)
        ' while',
        # wednesday  (949 firings)
        ' Wednesday',
        # tuesday  (908 firings)
        ' Tuesday',
        # monday  (835 firings)
        ' Monday',
        # today  (798 firings)
        ' today',
        # thursday  (776 firings)
        ' Thursday',
        # earli  (622 firings)
        ' earlier',
        # follow  (617 firings)
        ' following',
        # morn  (602 firings)
        ' morning',
        # via  (584 firings)
        ' via',
        # discus  (490 firings)
        ' discuss',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'on-family', 1

def prog_L06F21904(input_tokens):
    """38 token families, 44 surface forms (train F1 of the uncapped optimum: 0.816).
    Fires at 6,108 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to the term "Ter" in various contexts"""
    # --- end external annotation ---
    fire = {
        # ter  (1,153 firings)
        ' Ter', ' ter', 'Ter', ' TER',
        # tur  (270 firings)
        ' Tur',
        # zimbabwe  (210 firings)
        ' Zimbabwe',
        # terrain  (204 firings)
        ' terrain',
        # tier  (200 firings)
        ' Tier', 'Tier',
        # trafford  (185 firings)
        ' Trafford',
        # terr  (185 firings)
        ' terr', ' Terr',
        # mor  (159 firings)
        'Mor',
        # nut  (148 firings)
        ' Nut',
        # tor  (145 firings)
        ' tor',
        # ver  (127 firings)
        ' Vers',
        # uproar  (121 firings)
        ' uproar',
        # extrat  (118 firings)
        ' extrater',
        # mist  (110 firings)
        ' Mist',
        # tet  (107 firings)
        ' Tet',
        # tig  (88 firings)
        ' Tig',
        # sanct  (84 firings)
        ' sanct',
        # terra  (80 firings)
        ' Terra',
        # termin  (77 firings)
        'Termin', ' Termin',
        # tact  (65 firings)
        ' tact',
        # spur  (62 firings)
        ' Spur',
        # subt  (59 firings)
        ' subter',
        # ster  (55 firings)
        ' Ster',
        # ン  (49 firings)
        'ン',
        # zer  (45 firings)
        ' Zer',
        # vor  (40 firings)
        ' Vor',
        # retard  (38 firings)
        ' retard',
        # teaspoon  (37 firings)
        ' teaspoon',
        # territor  (37 firings)
        ' Territories',
        # alt  (34 firings)
        ' Alter',
        # tus  (33 firings)
        ' Tus',
        # ont  (30 firings)
        ' ont',
        # terran  (29 firings)
        ' Terran',
        # etiquette  (27 firings)
        ' etiquette',
        # pal  (23 firings)
        'Palest',
        # imbabwe  (22 firings)
        'imbabwe',
        # stellar  (21 firings)
        ' Stellar',
        # territ  (18 firings)
        ' Territ',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'ter-family', 1

def prog_L06F21905(input_tokens):
    """12 token families, 16 surface forms (train F1 of the uncapped optimum: 0.156).
    Fires at 28,901 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: emotional states related to safety, comfort, and feelings of guilt or exclusion"""
    # --- end external annotation ---
    fire = {
        # comfort  (289 firings)
        ' comfortable', ' comfort', ' comforting',
        # safe  (244 firings)
        ' safe', 'safe',
        # dead  (234 firings)
        ' dead',
        # bad  (180 firings)
        'bad',
        # confident  (113 firings)
        ' confident',
        # compell  (105 firings)
        ' compelled',
        # uncomfort  (95 firings)
        ' uncomfortable',
        # sad  (92 firings)
        ' sad', ' sadness',
        # honor  (89 firings)
        ' honored',
        # embarrass  (87 firings)
        ' embarrassed',
        # vulner  (87 firings)
        ' vulnerable',
        # lucky  (74 firings)
        ' lucky',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'comfort-family', 1

def prog_L06F21906(input_tokens):
    """17 token families, 19 surface forms (train F1 of the uncapped optimum: 0.182).
    Fires at 10,182 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: profanity and explicit language"""
    # --- end external annotation ---
    fire = {
        # *  (268 firings)
        '*',
        # ***  (123 firings)
        '***',
        # **  (113 firings)
        '**',
        # #  (95 firings)
        '#',
        # ü  (86 firings)
        'ü',
        # heck  (82 firings)
        ' heck',
        # odd  (69 firings)
        'odd',
        # ****  (64 firings)
        '****', ' ****',
        # ---  (59 firings)
        '---',
        # url  (58 firings)
        'url',
        # oth  (55 firings)
        'other',
        # ??  (37 firings)
        '??', ' ??',
        # ø  (36 firings)
        'ø',
        # )(  (30 firings)
        ')(',
        # pic  (29 firings)
        'pic',
        # ê  (28 firings)
        'ê',
        # ¢  (26 firings)
        '¢',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return '*-family', 1

def prog_L06F21907(input_tokens):
    """12 token families, 19 surface forms (train F1 of the uncapped optimum: 0.459).
    Fires at 7,935 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: instances of the word "reporting." """
    # --- end external annotation ---
    fire = {
        # report  (1,959 firings)
        ' reporting', ' Reporting', 'reported', 'reporting', 'report', ' REPORT', 'reports', 'Reporting',
        # storytell  (105 firings)
        ' storytelling',
        # rapp  (91 firings)
        ' Rapp',
        # organiz  (87 firings)
        ' organizing',
        # journalist  (79 firings)
        ' journalistic',
        # battalion  (51 firings)
        ' Battalion',
        # check  (38 firings)
        'checking',
        # pip  (35 firings)
        ' piping',
        # icing  (34 firings)
        'icing',
        # braz  (33 firings)
        ' Braz',
        # dropp  (30 firings)
        'dropping',
        # tell  (28 firings)
        'telling',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'report-family', 1

def prog_L06F21908(input_tokens):
    """44 token families, 102 surface forms (train F1 of the uncapped optimum: 0.421).
    Fires at 85,447 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: technical terms related to audio processing and monitoring"""
    # --- end external annotation ---
    fire = {
        # ing  (2,675 firings)
        'ing',
        # manage  (1,014 firings)
        ' management', ' Management', 'management', 'Management',
        # test  (788 firings)
        ' testing', ' Testing', 'testing', 'Testing', ' TEST',
        # search  (781 firings)
        ' search', ' Search', 'search', 'Search',
        # market  (714 firings)
        ' marketing', ' Marketing',
        # analysi  (682 firings)
        ' analysis', ' Analysis',
        # pay  (669 firings)
        ' payment', ' payments', ' Payments', ' Payment', 'payment',
        # shar  (668 firings)
        ' sharing', 'sharing', ' Sharing',
        # surveill  (626 firings)
        ' surveillance', ' Surveillance',
        # ation  (625 firings)
        'ation',
        # process  (620 firings)
        ' processing', ' Processing', 'processing',
        # iza  (592 firings)
        'ization',
        # track  (552 firings)
        ' tracking', 'tracking', ' Tracking',
        # learn  (547 firings)
        ' learning', ' Learning', 'learning',
        # park  (490 firings)
        ' parking', ' Parking',
        # storage  (475 firings)
        ' storage', ' Storage', 'storage',
        # min  (458 firings)
        ' mining', ' Mining', 'mining',
        # programm  (457 firings)
        ' programming', ' Programming',
        # vot  (451 firings)
        ' voting', ' Voting',
        # stream  (447 firings)
        ' streaming', ' Streaming', 'Streamer',
        # trad  (430 firings)
        ' trading', ' Trading',
        # combat  (410 firings)
        ' combat', ' Combat',
        # communica  (409 firings)
        ' communication', 'communication', ' Communication',
        # advertis  (403 firings)
        ' advertising', ' Advertising', 'advertising',
        # monitor  (388 firings)
        ' monitoring', ' Monitoring',
        # print  (359 firings)
        ' printing', ' Printing',
        # comput  (341 firings)
        ' computing', ' Computing',
        # delivery  (326 firings)
        ' delivery', ' Delivery',
        # manufactur  (304 firings)
        ' manufacturing', ' Manufacturing',
        # shipp  (294 firings)
        ' shipping', ' Shipping', 'Shipping',
        # light  (290 firings)
        ' lighting', ' Lighting', 'lighting',
        # dat  (286 firings)
        ' dating', ' Dating', 'dating',
        # messag  (284 firings)
        ' messaging', ' Messages',
        # encryp  (282 firings)
        ' encryption',
        # communication  (282 firings)
        ' communications', 'communications',
        # charg  (280 firings)
        ' charging', 'charging',
        # naviga  (258 firings)
        ' navigation', ' Navigation',
        # graphic  (244 firings)
        ' graphics',
        # imag  (241 firings)
        ' imaging', ' Imaging',
        # detec  (238 firings)
        ' detection', ' Detection',
        # omy  (235 firings)
        'omy',
        # recogni  (232 firings)
        ' recognition',
        # analytic  (229 firings)
        ' analytics', ' Analytics',
        # ifica  (221 firings)
        'ification',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'ing-family', 1

def prog_L06F21909(input_tokens):
    """12 token families, 17 surface forms (train F1 of the uncapped optimum: 0.745).
    Fires at 7,861 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to evidence or proof in various contexts"""
    # --- end external annotation ---
    fire = {
        # evid  (4,141 firings)
        ' evidence', ' Evidence', 'Evidence', 'evidence', ' evid',
        # proof  (436 firings)
        ' proof',
        # indication  (105 firings)
        ' indications',
        # empir  (88 firings)
        ' empirical', ' empir',
        # evidenc  (78 firings)
        ' evidenced',
        # testim  (42 firings)
        ' testim',
        # scripture  (36 firings)
        ' Scripture',
        # ________________________________  (33 firings)
        '________________________________',
        # circumst  (26 firings)
        ' circumst',
        # testimon  (24 firings)
        ' testimonies',
        # conclus  (23 firings)
        ' conclusive',
        # indi  (23 firings)
        ' indis',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'evid-family', 1

def prog_L06F21910(input_tokens):
    """44 token families, 53 surface forms (train F1 of the uncapped optimum: 0.791).
    Fires at 7,634 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: mentions of a specific name or title"""
    # --- end external annotation ---
    fire = {
        # motor  (508 firings)
        ' Motor', 'Motor',
        # nar  (506 firings)
        'nar', ' Nar', 'Nar', ' nar',
        # rodrigo  (264 firings)
        ' Rodrigo',
        # nav  (261 firings)
        ' Naval',
        # nissan  (199 firings)
        ' Nissan',
        # lar  (182 firings)
        ' Lar', ' lar',
        # nak  (164 firings)
        ' Nak',
        # agar  (154 firings)
        'agar',
        # viktor  (152 firings)
        ' Viktor',
        # swat  (136 firings)
        ' SWAT',
        # arri  (133 firings)
        ' Arri',
        # atl  (131 firings)
        ' Atl', 'Atl',
        # inspector  (125 firings)
        ' Inspector',
        # hyd  (122 firings)
        ' Hyder',
        # aru  (116 firings)
        'aru',
        # byrne  (106 firings)
        ' Byrne',
        # narc  (103 firings)
        ' Narc', ' narc',
        # aur  (90 firings)
        ' aur', ' Aur',
        # hak  (86 firings)
        ' Hak',
        # reimburse  (84 firings)
        ' reimburse', ' reimbursement',
        # hannib  (83 firings)
        ' Hannibal',
        # criminal  (81 firings)
        ' criminally',
        # kak  (75 firings)
        ' Kak',
        # inn  (69 firings)
        ' Inner',
        # andromeda  (68 firings)
        ' Andromeda',
        # metall  (68 firings)
        ' Metall',
        # out  (67 firings)
        ' Outer',
        # m  (66 firings)
        ' Mé',
        # subaru  (64 firings)
        ' Subaru',
        # naruto  (62 firings)
        ' Naruto',
        # ley  (61 firings)
        ' Ley',
        # orr  (58 firings)
        'orr',
        # sara  (57 firings)
        ' Saras',
        # stimul  (54 firings)
        ' stimul',
        # nora  (50 firings)
        ' Nora',
        # sher  (50 firings)
        ' sher',
        # ujah  (48 firings)
        'ujah',
        # lup  (47 firings)
        ' Lup',
        # alph  (45 firings)
        ' Alph',
        # iban  (44 firings)
        'iban',
        # reimb  (43 firings)
        ' reimb',
        # rem  (38 firings)
        ' REM',
        # narra  (35 firings)
        ' narration',
        # hyperten  (34 firings)
        ' hypertension',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'motor-family', 1

def prog_L06F21911(input_tokens):
    """3 token families, 10 surface forms (train F1 of the uncapped optimum: 0.232).
    Fires at 8,379 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: the word "who" indicating questions of identity or responsibility"""
    # --- end external annotation ---
    fire = {
        # who  (7,262 firings)
        ' who', ' Who', 'Who', 'who', ' WHO', 'WHO',
        # whoev  (216 firings)
        ' whoever', ' Whoever', 'Whoever',
        # omev  (21 firings)
        'omever',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'who-family', 1

def prog_L06F21912(input_tokens):
    """4 token families, 7 surface forms (train F1 of the uncapped optimum: 0.089).
    Fires at 168,708 of 36,786,566 positions.
    Fires at 0.46% of positions, and
    token rules do not serve features this dense: median test F1 0.086
    across the 37,173 features above 0.39% of positions, against 0.763 for
    the 76,283 below 0.016%. Read this fire set as the best available
    approximation, not as what the feature does."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: prominent political or social issues and activism-related terms"""
    # --- end external annotation ---
    fire = {
        # '  (2,439 firings)
        "'", " '",
        # :  (2,353 firings)
        ':',
        # trump  (746 firings)
        ' Trump', 'trump', ' TRUMP',
        # we  (490 firings)
        'We',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return "'-family", 1

def prog_L06F21913(input_tokens):
    """26 token families, 32 surface forms (train F1 of the uncapped optimum: 0.658).
    Fires at 5,105 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: instances of the phrase "READ MORE." """
    # --- end external annotation ---
    fire = {
        # read  (751 firings)
        'READ', ' READ',
        # man  (322 firings)
        'MAN',
        # ow  (285 firings)
        'OW',
        # get  (241 firings)
        'GET', ' GET',
        # watch  (207 firings)
        'WATCH', ' WATCH',
        # rawdownloadcloneembedreportprint  (204 firings)
        'rawdownloadcloneembedreportprint',
        # edit  (163 firings)
        'EDIT', ' EDIT',
        # share  (153 firings)
        'SHARE',
        # see  (128 firings)
        'SEE',
        # ual  (96 firings)
        'UAL',
        # new  (88 firings)
        'NEWS',
        # pol  (75 firings)
        'POL',
        # cet  (55 firings)
        ' CET',
        # list  (43 firings)
        'LIST',
        # just  (41 firings)
        'JUST',
        # pet  (39 firings)
        'PET',
        # sup  (37 firings)
        'SUP',
        # llow  (33 firings)
        'LLOW',
        # pre  (31 firings)
        'PRE',
        # ull  (29 firings)
        'ULL',
        # ►  (24 firings)
        '►',
        # now  (24 firings)
        'NOW',
        # rep  (22 firings)
        'REP', 'reply',
        # sign  (19 firings)
        'SIGN',
        # raw  (15 firings)
        'RAW',
        # fix  (14 firings)
        ' FIX', 'FIX',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'read-family', 1

def prog_L06F21914(input_tokens):
    """1 token families, 2 surface forms (train F1 of the uncapped optimum: 0.166).
    Fires at 134,711 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: occurrences of the word "the." """
    # --- end external annotation ---
    fire = {
        # the  (123,949 firings)
        ' the', ' THE',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'the-family', 1

def prog_L06F21915(input_tokens):
    """32 token families, 33 surface forms (train F1 of the uncapped optimum: 0.791).
    Fires at 6,507 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: occurrences of the name "Austin" in various contexts"""
    # --- end external annotation ---
    fire = {
        # austin  (1,325 firings)
        ' Austin', 'Austin',
        # antonio  (528 firings)
        ' Antonio',
        # bank  (240 firings)
        ' Banks',
        # sheffield  (197 firings)
        ' Sheffield',
        # ut  (178 firings)
        ' UT',
        # bristol  (176 firings)
        ' Bristol',
        # cain  (170 firings)
        ' Cain',
        # barton  (145 firings)
        ' Barton',
        # xton  (145 firings)
        'xton',
        # williamson  (143 firings)
        ' Williamson',
        # sx  (109 firings)
        ' SX',
        # cork  (109 firings)
        ' Cork',
        # cbd  (102 firings)
        ' CBD',
        # bangalore  (101 firings)
        ' Bangalore',
        # pax  (93 firings)
        ' PAX',
        # beck  (89 firings)
        ' Becker',
        # amar  (86 firings)
        ' Amar',
        # burges  (86 firings)
        ' Burgess',
        # cedar  (86 firings)
        ' Cedar',
        # ashton  (85 firings)
        ' Ashton',
        # oak  (84 firings)
        ' oak',
        # cary  (83 firings)
        ' Cary',
        # ci  (81 firings)
        ' Ci',
        # vaughan  (79 firings)
        ' Vaughan',
        # aign  (74 firings)
        'aign',
        # augusta  (49 firings)
        ' Augusta',
        # dain  (38 firings)
        'dain',
        # ageddon  (35 firings)
        'ageddon',
        # aust  (28 firings)
        ' aust',
        # avalon  (27 firings)
        ' Avalon',
        # acs  (21 firings)
        ' ACS',
        # avocado  (18 firings)
        ' avocado',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'austin-family', 1

def prog_L06F21916(input_tokens):
    """40 token families, 45 surface forms (train F1 of the uncapped optimum: 0.639).
    Fires at 7,372 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to the Eiffel Tower"""
    # --- end external annotation ---
    fire = {
        # iff  (1,164 firings)
        'iff', 'iffs', 'IFF',
        # few  (170 firings)
        'Few', 'few',
        # cliff  (148 firings)
        ' Cliff',
        # sniff  (137 firings)
        ' sniff',
        # sec  (131 firings)
        ' Sec',
        # judy  (111 firings)
        ' Judy',
        # britt  (99 firings)
        ' Britt',
        # tiffany  (92 firings)
        ' Tiffany',
        # rict  (91 firings)
        'rict',
        # forty  (86 firings)
        ' Forty',
        # icket  (85 firings)
        'icket',
        # tariff  (84 firings)
        ' tariff',
        # mob  (84 firings)
        ' Mob',
        # schiff  (82 firings)
        ' Schiff',
        # iem  (82 firings)
        'iem',
        # iffin  (79 firings)
        'iffin',
        # ticket  (78 firings)
        ' Ticket',
        # pip  (69 firings)
        ' Piper',
        # supp  (66 firings)
        ' supp',
        # arge  (65 firings)
        'arge',
        # riff  (64 firings)
        ' riff',
        # iola  (63 firings)
        'iola',
        # thirty  (63 firings)
        ' Thirty',
        # ruff  (59 firings)
        'ruff',
        # atel  (57 firings)
        'atel',
        # diff  (55 firings)
        'Diff', ' Diff',
        # clifford  (51 firings)
        ' Clifford',
        # ipt  (46 firings)
        'ipt',
        # mf  (40 firings)
        ' MF', 'MF',
        # bey  (34 firings)
        'Bey',
        # griff  (33 firings)
        ' Griff',
        # prejud  (31 firings)
        ' prejud',
        # iffe  (30 firings)
        'iffe',
        # ishop  (29 firings)
        'ishop',
        # igg  (26 firings)
        'igger',
        # mism  (24 firings)
        ' mism',
        # aund  (24 firings)
        'aund',
        # font  (22 firings)
        'Font',
        # byte  (22 firings)
        ' byte',
        # tiff  (21 firings)
        ' Tiff',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'iff-family', 1

def prog_L06F21917(input_tokens):
    """14 token families, 25 surface forms (train F1 of the uncapped optimum: 0.156).
    Fires at 708,064 of 36,786,566 positions.
    Fires at 1.92% of positions, and
    token rules do not serve features this dense: median test F1 0.086
    across the 37,173 features above 0.39% of positions, against 0.763 for
    the 76,283 below 0.016%. Read this fire set as the best available
    approximation, not as what the feature does."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to events involving conflict or violence"""
    # --- end external annotation ---
    fire = {
        # a  (33,172 firings)
        ' a',
        # has  (8,737 firings)
        ' has',
        # by  (7,103 firings)
        ' by',
        # aft  (6,628 firings)
        ' after',
        # been  (4,969 firings)
        ' been',
        # week  (4,804 firings)
        ' week', ' weeks', 'week',
        # which  (3,530 firings)
        ' which',
        # month  (3,010 firings)
        ' month', ' months', 'month', ' Months', 'months',
        # day  (2,745 firings)
        ' days', ' day', 'day', 'Days',
        # recent  (2,462 firings)
        ' recent', ' recently', ' Recently',
        # in  (2,415 firings)
        'In',
        # year  (2,357 firings)
        ' year',
        # accord  (2,232 firings)
        ' according',
        # since  (1,908 firings)
        ' since',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'a-family', 1

def prog_L06F21918(input_tokens):
    """19 token families, 48 surface forms (train F1 of the uncapped optimum: 0.213).
    Fires at 177,013 of 36,786,566 positions.
    Fires at 0.48% of positions, and
    token rules do not serve features this dense: median test F1 0.086
    across the 37,173 features above 0.39% of positions, against 0.763 for
    the 76,283 below 0.016%. Read this fire set as the best available
    approximation, not as what the feature does."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to reports and analyses"""
    # --- end external annotation ---
    fire = {
        # report  (6,088 firings)
        ' report', ' reports', ' reported', ' reporter', ' Report', ' reporting', ' Reports', ' REPORT',
        # rul  (1,348 firings)
        ' rules', ' ruling', ' ruled', ' Rules', ' rulings',
        # research  (1,344 firings)
        ' research', ' researchers', ' Research', ' researcher',
        # data  (1,212 firings)
        ' data',
        # law  (1,129 firings)
        ' law',
        # poll  (1,025 firings)
        ' poll', ' Poll', ' polling',
        # deci  (1,003 firings)
        ' decision', ' Decision',
        # investiga  (930 firings)
        ' investigation',
        # meet  (859 firings)
        ' meeting', ' meetings', ' Meeting',
        # plan  (809 firings)
        ' plan',
        # policy  (767 firings)
        ' policy',
        # fund  (733 firings)
        ' funding', ' funds', ' Funding', ' Funds',
        # docu  (690 firings)
        ' documents', ' document', ' Documents',
        # website  (617 firings)
        ' website',
        # analysi  (562 firings)
        ' analysis', ' Analysis', 'analysis',
        # response  (504 firings)
        ' response', ' Response',
        # effort  (494 firings)
        ' efforts',
        # coverage  (492 firings)
        ' coverage', ' Coverage',
        # survey  (445 firings)
        ' survey', ' surveys',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'report-family', 1

def prog_L06F21919(input_tokens):
    """38 token families, 64 surface forms (train F1 of the uncapped optimum: 0.408).
    Fires at 104,899 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: gerunds and present participles that emphasize ongoing actions or processes"""
    # --- end external annotation ---
    fire = {
        # mak  (2,699 firings)
        ' making', 'Making', ' Making',
        # being  (2,110 firings)
        ' being',
        # gett  (2,001 firings)
        ' getting', 'Getting', ' Getting', 'getting',
        # creat  (1,190 firings)
        ' creating', ' Creating', 'Creating',
        # hav  (1,156 firings)
        ' having',
        # tak  (1,128 firings)
        ' taking',
        # play  (1,073 firings)
        ' playing', ' Playing',
        # build  (1,028 firings)
        ' building', 'Building',
        # putt  (938 firings)
        ' putting', 'Putting', ' Putting',
        # help  (768 firings)
        ' helping',
        # provid  (726 firings)
        ' providing',
        # keep  (725 firings)
        ' keeping', 'Keeping', ' Keeping',
        # giv  (689 firings)
        ' giving', 'Giving', ' Giving',
        # bring  (683 firings)
        ' bringing', ' Bringing',
        # find  (674 firings)
        ' finding', ' Finding', 'finding',
        # develop  (648 firings)
        ' developing',
        # writ  (595 firings)
        ' writing',
        # winn  (585 firings)
        ' winning',
        # see  (535 firings)
        ' seeing', ' Seeing', 'Seeing', 'seeing',
        # sell  (531 firings)
        ' selling', ' Selling',
        # kill  (529 firings)
        ' killing',
        # pay  (527 firings)
        ' paying',
        # protect  (457 firings)
        ' protecting',
        # support  (436 firings)
        ' supporting', ' Supporting',
        # los  (426 firings)
        ' losing',
        # improv  (414 firings)
        ' improving',
        # rais  (414 firings)
        ' raising',
        # buy  (393 firings)
        ' buying',
        # reduc  (374 firings)
        ' reducing',
        # pass  (355 firings)
        ' passing', ' Passing', ' Passed',
        # enter  (352 firings)
        ' entering',
        # send  (338 firings)
        ' sending', ' Sending',
        # promot  (319 firings)
        ' promoting',
        # fail  (307 firings)
        ' failing',
        # deal  (303 firings)
        ' dealing',
        # produc  (298 firings)
        ' producing',
        # remov  (267 firings)
        ' removing',
        # reach  (267 firings)
        ' reaching',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'mak-family', 1

def prog_L06F21920(input_tokens):
    """6 token families, 10 surface forms (train F1 of the uncapped optimum: 0.754).
    Fires at 6,832 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to the word "Me." """
    # --- end external annotation ---
    fire = {
        # me  (4,107 firings)
        ' Me', 'me', 'Me', ' ME', 'ME',
        # megan  (186 firings)
        ' Megan',
        # meh  (123 firings)
        ' Meh',
        # measl  (108 firings)
        ' measles',
        # moe  (38 firings)
        ' Moe',
        # mei  (28 firings)
        ' Mei',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'me-family', 1

def prog_L06F21921(input_tokens):
    """2 token families, 7 surface forms (train F1 of the uncapped optimum: 0.067).
    Fires at 33,260 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: phrases expressing intentions or desires to take action"""
    # --- end external annotation ---
    fire = {
        # to  (24,368 firings)
        ' to', 'to', ' To', ' TO',
        # should  (597 firings)
        ' should', 'should', ' SHOULD',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'to-family', 1

def prog_L06F21922(input_tokens):
    """36 token families, 44 surface forms (train F1 of the uncapped optimum: 0.650).
    Fires at 8,645 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: occurrences of the word "poster" and its variations"""
    # --- end external annotation ---
    fire = {
        # post  (891 firings)
        ' poster', ' posters', ' Poster',
        # ost  (463 firings)
        'oster',
        # billboard  (278 firings)
        ' billboard', ' billboards',
        # mur  (224 firings)
        ' mural', ' mur',
        # pul  (206 firings)
        ' Pul',
        # fly  (176 firings)
        ' flyers', ' flyer',
        # fram  (156 firings)
        ' framed',
        # comment  (149 firings)
        ' commenters', ' commenter',
        # stick  (148 firings)
        ' sticker',
        # paramount  (147 firings)
        ' Paramount',
        # board  (146 firings)
        'boards',
        # infograph  (132 firings)
        ' infographic',
        # pos  (111 firings)
        ' posing',
        # pap  (110 firings)
        'paper', 'papers',
        # vide  (109 firings)
        ' vide', ' Vide',
        # bump  (102 firings)
        ' bumper',
        # aper  (99 firings)
        'aper',
        # presentation  (85 firings)
        ' presentations',
        # pal  (81 firings)
        'pal',
        # bulletin  (80 firings)
        ' bulletin',
        # pic  (78 firings)
        ' pics',
        # print  (70 firings)
        ' prints',
        # pad  (69 firings)
        'pad',
        # projector  (67 firings)
        ' projector',
        # pcb  (60 firings)
        ' PCB',
        # wallpap  (58 firings)
        ' wallpaper',
        # sten  (48 firings)
        ' sten',
        # resur  (47 firings)
        ' resur',
        # crucifix  (40 firings)
        ' crucifix',
        # plast  (37 firings)
        ' plaster',
        # pter  (29 firings)
        'pter',
        # powerpoint  (28 firings)
        ' PowerPoint',
        # posterior  (26 firings)
        ' posterior',
        # pall  (25 firings)
        ' pall',
        # thumbnail  (23 firings)
        ' Thumbnails',
        # mod  (23 firings)
        ' Moder',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'post-family', 1

def prog_L06F21923(input_tokens):
    """12 token families, 17 surface forms (train F1 of the uncapped optimum: 0.384).
    Fires at 8,338 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: concepts and discussions centered around significance or importance"""
    # --- end external annotation ---
    fire = {
        # matt  (2,191 firings)
        ' matter', ' matters', ' Matter', ' Matters', 'matter',
        # appl  (214 firings)
        ' applies',
        # loom  (104 firings)
        ' looms',
        # car  (93 firings)
        ' cares',
        # suck  (89 firings)
        ' sucks',
        # matter  (57 firings)
        ' mattered',
        # rang  (47 firings)
        ' rang',
        # mat  (35 firings)
        ' MAT',
        # suffice  (34 firings)
        ' suffice',
        # palp  (30 firings)
        ' palpable',
        # paramount  (25 firings)
        ' paramount',
        # tain  (21 firings)
        'tains', 'tained',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'matt-family', 1

def prog_L06F21924(input_tokens):
    """1 token families, 1 surface forms (train F1 of the uncapped optimum: 0.264).
    Fires at 25,985 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: the word "described" and its associated phrases"""
    # --- end external annotation ---
    fire = {
        # as  (22,139 firings)
        ' as',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'as-family', 1

def prog_L06F21925(input_tokens):
    """2 token families, 3 surface forms (train F1 of the uncapped optimum: 0.639).
    Fires at 9,841 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to links or connections in various contexts"""
    # --- end external annotation ---
    fire = {
        # between  (8,657 firings)
        ' between', ' Between',
        # pmwiki  (52 firings)
        'pmwiki',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'between-family', 1

def prog_L06F21926(input_tokens):
    """44 token families, 52 surface forms (train F1 of the uncapped optimum: 0.555).
    Fires at 8,340 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: terms related to confessions and admission of guilt"""
    # --- end external annotation ---
    fire = {
        # confes  (268 firings)
        ' confess', ' confession',
        # pact  (232 firings)
        ' pact', ' Pact',
        # shawn  (213 firings)
        ' Shawn',
        # confess  (203 firings)
        ' confessed',
        # reve  (165 firings)
        ' Reve', 'reve',
        # sud  (141 firings)
        ' Sud',
        # rudy  (136 firings)
        ' Rudy',
        # candid  (133 firings)
        ' candid',
        # ession  (129 firings)
        'ession', 'essional',
        # contr  (123 firings)
        ' contr',
        # admitt  (96 firings)
        ' admitting',
        # betray  (90 firings)
        ' betray', ' betrayed',
        # bragg  (88 firings)
        ' bragging',
        # seces  (86 firings)
        ' secession',
        # raw  (83 firings)
        ' RAW',
        # volunteer  (75 firings)
        ' volunteered',
        # sin  (70 firings)
        ' sins',
        # profes  (69 firings)
        ' profess',
        # bapt  (65 firings)
        ' baptized', ' Bapt', ' bapt',
        # confession  (55 firings)
        ' confessions',
        # pas  (55 firings)
        ' Passion',
        # calvin  (55 firings)
        ' Calvin',
        # crocod  (47 firings)
        ' crocod',
        # tid  (43 firings)
        ' Tid',
        # declaration  (43 firings)
        ' declarations',
        # boast  (43 firings)
        ' boasting',
        # remorse  (42 firings)
        ' remorse',
        # couch  (42 firings)
        ' Couch',
        # nath  (40 firings)
        ' Nath',
        # dah  (39 firings)
        ' Dah',
        # akable  (38 firings)
        'akable',
        # baptism  (37 firings)
        ' baptism',
        # blush  (37 firings)
        ' blush',
        # incrim  (35 firings)
        ' incrim',
        # chenko  (34 firings)
        'chenko',
        # freud  (34 firings)
        ' Freud',
        # cassette  (33 firings)
        ' cassette',
        # cyan  (32 firings)
        ' cyan',
        # itent  (31 firings)
        'itent',
        # autobi  (26 firings)
        ' autobi',
        # weep  (26 firings)
        ' weep',
        # repent  (26 firings)
        ' repent', ' repentance',
        # conv  (25 firings)
        'conv',
        # trembl  (21 firings)
        ' trembling',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'confes-family', 1

def prog_L06F21927(input_tokens):
    """4 token families, 10 surface forms (train F1 of the uncapped optimum: 0.801).
    Fires at 12,345 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to various medical or training centers"""
    # --- end external annotation ---
    fire = {
        # cent  (7,373 firings)
        ' Center', ' center', ' centers', 'Center', 'center', ' CENT',
        # centre  (2,038 firings)
        ' Centre', ' centre',
        # centr  (262 firings)
        ' centres',
        # appeal  (225 firings)
        ' Appeals',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'cent-family', 1

def prog_L06F21928(input_tokens):
    """5 token families, 6 surface forms (train F1 of the uncapped optimum: 0.272).
    Fires at 7,791 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: instances of the phrase "break down." """
    # --- end external annotation ---
    fire = {
        # down  (3,296 firings)
        ' down', 'down',
        # breakdown  (348 firings)
        ' breakdown',
        # lat  (77 firings)
        'lated',
        # bord  (34 firings)
        'border',
        # struct  (33 firings)
        'struct',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'down-family', 1

def prog_L06F21929(input_tokens):
    """41 token families, 42 surface forms (train F1 of the uncapped optimum: 0.239).
    Fires at 204,601 of 36,786,566 positions.
    Fires at 0.56% of positions, and
    token rules do not serve features this dense: median test F1 0.086
    across the 37,173 features above 0.39% of positions, against 0.763 for
    the 76,283 below 0.016%. Read this fire set as the best available
    approximation, not as what the feature does."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: specific dates and times in the text"""
    # --- end external annotation ---
    fire = {
        # year  (4,515 firings)
        ' year',
        # last  (4,295 firings)
        ' last',
        # week  (3,606 firings)
        ' week',
        # ago  (2,844 firings)
        ' ago',
        # monday  (2,656 firings)
        ' Monday',
        # tuesday  (2,656 firings)
        ' Tuesday',
        # wednesday  (2,446 firings)
        ' Wednesday',
        # friday  (2,259 firings)
        ' Friday',
        # thursday  (2,192 firings)
        ' Thursday',
        # month  (1,935 firings)
        ' month',
        # night  (1,721 firings)
        ' night',
        # sunday  (1,683 firings)
        ' Sunday',
        # saturday  (1,554 firings)
        ' Saturday',
        # march  (1,520 firings)
        ' March',
        # may  (1,507 firings)
        ' May',
        # 2015  (1,496 firings)
        ' 2015',
        # morn  (1,449 firings)
        ' morning',
        # late  (1,391 firings)
        ' late', ' lately',
        # july  (1,370 firings)
        ' July',
        # june  (1,310 firings)
        ' June',
        # 2014  (1,281 firings)
        ' 2014',
        # 2012  (1,208 firings)
        ' 2012',
        # 2013  (1,182 firings)
        ' 2013',
        # septemb  (1,122 firings)
        ' September',
        # january  (1,115 firings)
        ' January',
        # april  (1,110 firings)
        ' April',
        # octob  (1,089 firings)
        ' October',
        # august  (1,066 firings)
        ' August',
        # 2011  (1,053 firings)
        ' 2011',
        # novemb  (1,003 firings)
        ' November',
        # earli  (933 firings)
        ' earlier',
        # weekend  (932 firings)
        ' weekend',
        # afternoon  (928 firings)
        ' afternoon',
        # 2010  (897 firings)
        ' 2010',
        # decemb  (892 firings)
        ' December',
        # february  (891 firings)
        ' February',
        # 2008  (742 firings)
        ' 2008',
        # summ  (737 firings)
        ' summer',
        # 2009  (691 firings)
        ' 2009',
        # yesterday  (631 firings)
        ' yesterday',
        # 2007  (557 firings)
        ' 2007',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'year-family', 1

def prog_L06F21930(input_tokens):
    """6 token families, 6 surface forms (train F1 of the uncapped optimum: 0.158).
    Fires at 99,073 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: phrases indicating requests or actions taken by groups of people"""
    # --- end external annotation ---
    fire = {
        # are  (13,534 firings)
        ' are',
        # have  (11,047 firings)
        ' have',
        # were  (4,699 firings)
        ' were',
        # often  (782 firings)
        ' often',
        # aren  (320 firings)
        ' aren',
        # seem  (268 firings)
        ' seem',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'are-family', 1

def prog_L06F21931(input_tokens):
    """7 token families, 12 surface forms (train F1 of the uncapped optimum: 0.070).
    Fires at 159,610 of 36,786,566 positions.
    Fires at 0.43% of positions, and
    token rules do not serve features this dense: median test F1 0.086
    across the 37,173 features above 0.39% of positions, against 0.763 for
    the 76,283 below 0.016%. Read this fire set as the best available
    approximation, not as what the feature does."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: phrases related to action-oriented themes and activities"""
    # --- end external annotation ---
    fire = {
        # ,  (16,761 firings)
        ',',
        # (  (2,063 firings)
        ' (',
        # against  (1,061 firings)
        ' against', ' Against',
        # close  (827 firings)
        'CLOSE',
        # between  (761 firings)
        ' between',
        # action  (517 firings)
        ' action', ' actions', 'actions',
        # involv  (510 firings)
        ' involving', ' involved', ' involves',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return ',-family', 1

def prog_L06F21932(input_tokens):
    """29 token families, 31 surface forms (train F1 of the uncapped optimum: 0.806).
    Fires at 4,326 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: occurrences of the prefix "com" in various contexts"""
    # --- end external annotation ---
    fire = {
        # com  (1,171 firings)
        ' com', ' Com', ' COM',
        # comm  (339 firings)
        ' comm',
        # comet  (195 firings)
        ' comet',
        # coma  (123 firings)
        ' coma',
        # gru  (106 firings)
        ' gru',
        # android  (92 firings)
        ' android',
        # org  (89 firings)
        ' org',
        # comple  (73 firings)
        ' comple',
        # emer  (73 firings)
        ' emer',
        # carmen  (68 firings)
        ' Carmen',
        # incon  (63 firings)
        ' incon',
        # benign  (63 firings)
        ' benign',
        # java  (61 firings)
        ' java',
        # consum  (57 firings)
        ' consum',
        # uncom  (56 firings)
        ' uncom',
        # ris  (53 firings)
        ' ris',
        # congen  (52 firings)
        ' congen',
        # rock  (51 firings)
        ' rocking',
        # prod  (46 firings)
        ' prod',
        # sust  (38 firings)
        ' sust',
        # accu  (38 firings)
        ' accus',
        # indi  (36 firings)
        ' indis',
        # incom  (32 firings)
        ' incom',
        # י�  (25 firings)
        'י�',
        # brun  (24 firings)
        ' brun',
        # produ  (15 firings)
        ' produ',
        # evid  (14 firings)
        ' evid',
        # unimagin  (14 firings)
        ' unimagin',
        # educ  (11 firings)
        ' educ',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'com-family', 1

def prog_L06F21933(input_tokens):
    """49 token families, 52 surface forms (train F1 of the uncapped optimum: 0.687).
    Fires at 11,481 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: mentions of memorials or commemorative events"""
    # --- end external annotation ---
    fire = {
        # memor  (915 firings)
        ' Memorial', ' memorial',
        # independ  (361 firings)
        ' Independence',
        # cyb  (305 firings)
        ' Cyber',
        # veteran  (198 firings)
        ' Veterans',
        # holiday  (190 firings)
        ' Holiday',
        # trophy  (179 firings)
        ' Trophy',
        # lobby  (168 firings)
        ' lobby',
        # civ  (155 firings)
        ' Civic',
        # monu  (153 firings)
        ' Monument',
        # mem  (143 firings)
        'Mem', ' MEM',
        # parkway  (142 firings)
        ' Parkway',
        # emb  (140 firings)
        'EMBER',
        # coliseum  (132 firings)
        ' Coliseum',
        # clara  (132 firings)
        ' Clara',
        # jurass  (128 firings)
        ' Jurassic',
        # highland  (125 firings)
        ' Highland', ' Highlands',
        # huntington  (119 firings)
        ' Huntington',
        # wembley  (115 firings)
        ' Wembley',
        # governor  (107 firings)
        ' Governors',
        # harbor  (105 firings)
        ' Harbor',
        # hampton  (101 firings)
        ' Hampton',
        # president  (101 firings)
        ' Presidents',
        # account  (101 firings)
        ' Accountability',
        # bump  (99 firings)
        ' bumper',
        # rockefell  (87 firings)
        ' Rockefeller',
        # hancock  (78 firings)
        ' Hancock',
        # glaci  (77 firings)
        ' Glacier',
        # harbour  (77 firings)
        ' Harbour',
        # maritime  (76 firings)
        ' Maritime',
        # hamm  (72 firings)
        ' Hammer',
        # friendship  (71 firings)
        ' Friendship',
        # umm  (71 firings)
        'ummer',
        # buckingham  (67 firings)
        ' Buckingham',
        # remem  (65 firings)
        ' Remem',
        # lunar  (65 firings)
        ' Lunar',
        # statue  (63 firings)
        ' Statue',
        # mgm  (63 firings)
        ' MGM',
        # rsa  (61 firings)
        ' RSA',
        # clapp  (61 firings)
        ' Clapper',
        # lucky  (61 firings)
        ' Lucky',
        # hamp  (57 firings)
        ' Hamp',
        # missile  (55 firings)
        ' Missile',
        # cyp  (54 firings)
        ' Cyp',
        # lawn  (54 firings)
        ' Lawn',
        # umann  (54 firings)
        'umann',
        # countdown  (51 firings)
        ' Countdown',
        # neurolog  (50 firings)
        ' Neurolog',
        # lutheran  (47 firings)
        ' Lutheran',
        # lazaru  (41 firings)
        ' Lazarus',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'memor-family', 1

def prog_L06F21934(input_tokens):
    """39 token families, 48 surface forms (train F1 of the uncapped optimum: 0.714).
    Fires at 5,511 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: instances of the word "gro" indicating themes of growth or collectivism"""
    # --- end external annotation ---
    fire = {
        # gro  (807 firings)
        ' Gro', ' gro', 'gro', 'Gro',
        # agan  (384 firings)
        'agan',
        # grove  (223 firings)
        ' Grove',
        # fro  (221 firings)
        ' Fro', ' fro',
        # thro  (191 firings)
        'thro', ' thro', ' Thro',
        # groom  (156 firings)
        ' groom', ' grooming',
        # isco  (127 firings)
        'isco',
        # fo  (126 firings)
        'FO',
        # gri  (100 firings)
        ' Gri', ' gri',
        # ockey  (92 firings)
        'ockey',
        # groin  (89 firings)
        ' groin',
        # blo  (71 firings)
        ' blo',
        # heel  (65 firings)
        ' heel',
        # gi  (61 firings)
        'GI',
        # gymn  (59 firings)
        ' gymn',
        # headach  (55 firings)
        ' headaches',
        # flo  (52 firings)
        ' flo',
        # shri  (49 firings)
        ' shri',
        # lou  (49 firings)
        ' lou',
        # gra  (46 firings)
        'Gra',
        # gasp  (46 firings)
        ' gasp', ' gasped',
        # hob  (46 firings)
        ' hob',
        # funk  (45 firings)
        ' funk',
        # agon  (43 firings)
        ' agon',
        # groove  (42 firings)
        ' groove',
        # gh  (40 firings)
        ' GH',
        # awkward  (39 firings)
        ' awkwardly',
        # grun  (38 firings)
        ' grun',
        # grape  (30 firings)
        ' grape',
        # jo  (28 firings)
        'JO',
        # atro  (28 firings)
        ' atro',
        # invol  (27 firings)
        ' invol',
        # stag  (26 firings)
        ' stag',
        # grou  (25 firings)
        ' grou',
        # impro  (20 firings)
        ' impro',
        # grunt  (17 firings)
        ' grunt',
        # flatt  (17 firings)
        ' flatt',
        # gre  (17 firings)
        'gre',
        # eal  (15 firings)
        'eals',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'gro-family', 1

def prog_L06F21935(input_tokens):
    """24 token families, 93 surface forms (train F1 of the uncapped optimum: 0.289).
    Fires at 161,736 of 36,786,566 positions.
    Fires at 0.44% of positions, and
    token rules do not serve features this dense: median test F1 0.086
    across the 37,173 features above 0.39% of positions, against 0.763 for
    the 76,283 below 0.016%. Read this fire set as the best available
    approximation, not as what the feature does."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to hardback and limited edition printed materials"""
    # --- end external annotation ---
    fire = {
        # book  (3,467 firings)
        ' book', ' books', 'book', 'books', 'Books', 'Book', 'BOOK',
        # edi  (1,746 firings)
        ' edition', ' Edition', 'edition', ' EDITION',
        # ser  (1,701 firings)
        ' series', 'series', ' serial',
        # release  (1,270 firings)
        ' release', 'release', 'Release',
        # ver  (1,137 firings)
        ' version',
        # collec  (1,067 firings)
        ' collection', ' Collection', 'collection', 'Collection',
        # short  (943 firings)
        ' short', ' shorts',
        # pack  (932 firings)
        ' pack', ' Pack', ' packs', ' Packs', 'pack', 'packs', 'Pack', ' PACK',
        # album  (919 firings)
        ' album', ' albums', 'album',
        # origin  (881 firings)
        ' original', ' Original', 'original',
        # cov  (805 firings)
        ' cover', ' covers', 'cover', ' Cover', 'Cover', ' COVER',
        # print  (740 firings)
        ' print', ' printed', ' prints', 'print', 'prints', 'printed', ' Printed',
        # limit  (683 firings)
        ' limited', ' Limited', 'Limited', 'limited', ' LIMITED',
        # digit  (666 firings)
        ' digital', ' digit', 'Digital', 'digital',
        # novel  (611 firings)
        ' novel', ' novels', ' Novel',
        # class  (523 firings)
        ' classic', ' Classic', 'Classic', 'classic',
        # disc  (488 firings)
        ' disc', ' Disc', 'disc', ' discs', 'Disc',
        # com  (479 firings)
        ' comic',
        # set  (466 firings)
        ' sets', ' Set', ' Sets', 'sets',
        # releas  (453 firings)
        ' releases', 'released', ' Releases',
        # download  (452 firings)
        ' download', ' downloadable', ' downloads', ' Downloads',
        # volume  (412 firings)
        ' volume', ' Volume', 'Volume', 'volume',
        # dvd  (409 firings)
        ' DVD', 'DVD', ' DVDs',
        # featur  (405 firings)
        ' featuring', ' Featuring',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'book-family', 1

def prog_L06F21936(input_tokens):
    """40 token families, 57 surface forms (train F1 of the uncapped optimum: 0.364).
    Fires at 62,793 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to specific sports organizations and competitions"""
    # --- end external annotation ---
    fire = {
        # league  (2,214 firings)
        ' League', 'League', 'league',
        # l  (913 firings)
        'L',
        # nba  (720 firings)
        ' NBA', 'NBA',
        # fc  (709 firings)
        ' FC', 'FC',
        # cup  (667 firings)
        ' Cup', 'cup',
        # socc  (557 firings)
        ' Soccer',
        # championship  (551 firings)
        ' Championship',
        # mls  (510 firings)
        ' MLS',
        # ba  (467 firings)
        'BA',
        # rugby  (451 firings)
        ' Rugby', ' rugby',
        # basketball  (448 firings)
        ' basketball', ' Basketball',
        # ser  (429 firings)
        ' Series', 'Series',
        # hockey  (400 firings)
        ' Hockey',
        # test  (392 firings)
        ' Test', 'Test',
        # port  (354 firings)
        'port', 'ports',
        # open  (351 firings)
        ' Open',
        # afl  (345 firings)
        ' AFL',
        # sec  (334 firings)
        ' SEC', 'SEC',
        # nhl  (308 firings)
        ' NHL',
        # hl  (296 firings)
        'HL',
        # bc  (296 firings)
        'BC',
        # ac  (294 firings)
        'AC',
        # tour  (293 firings)
        ' Tour', 'Tour', ' TOUR',
        # nrl  (268 firings)
        ' NRL',
        # fl  (257 firings)
        'FL',
        # gp  (252 firings)
        'GP', ' GP',
        # ga  (250 firings)
        'GA',
        # cs  (228 firings)
        'CS',
        # weight  (228 firings)
        'weight',
        # universe  (215 firings)
        ' Universe',
        # ten  (211 firings)
        ' Ten',
        # ollywood  (203 firings)
        'ollywood',
        # ma  (198 firings)
        'MA',
        # gt  (189 firings)
        ' GT',
        # bo  (188 firings)
        'BO',
        # sport  (183 firings)
        'Sports', 'sports', ' SPORTS',
        # fa  (181 firings)
        'FA',
        # acc  (178 firings)
        ' ACC', 'ACC',
        # rac  (164 firings)
        ' Racing',
        # baseball  (158 firings)
        ' Baseball',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'league-family', 1

def prog_L06F21937(input_tokens):
    """1 token families, 3 surface forms (train F1 of the uncapped optimum: 0.326).
    Fires at 59,090 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: phrases that start with "one thing that" to identify key points or themes"""
    # --- end external annotation ---
    fire = {
        # that  (53,509 firings)
        ' that', ' THAT', ' thats',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'that-family', 1

def prog_L06F21938(input_tokens):
    """2 token families, 4 surface forms (train F1 of the uncapped optimum: 0.490).
    Fires at 15,994 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: the phrase "at the end of the day." """
    # --- end external annotation ---
    fire = {
        # day  (8,048 firings)
        ' day', 'Day', ' DAY',
        # pt  (344 firings)
        'pt',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'day-family', 1

def prog_L06F21939(input_tokens):
    """49 token families, 64 surface forms (train F1 of the uncapped optimum: 0.707).
    Fires at 18,358 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: mentions of the name "Crow." """
    # --- end external annotation ---
    fire = {
        # hawk  (346 firings)
        ' Hawks', ' hawk', ' Hawk',
        # crow  (310 firings)
        ' Crow', ' crow', 'crow',
        # buck  (292 firings)
        ' Buck',
        # lgbtq  (258 firings)
        ' LGBTQ',
        # jew  (252 firings)
        ' Jew', 'Jew',
        # brow  (251 firings)
        ' Brow', ' brow', 'Brow', 'brow',
        # chrom  (246 firings)
        ' Chrom', ' chrom',
        # counsel  (242 firings)
        ' Counsel',
        # chain  (213 firings)
        ' chains', ' Chains',
        # bowie  (194 firings)
        ' Bowie',
        # schneid  (194 firings)
        ' Schneider',
        # divis  (186 firings)
        ' divisive',
        # kes  (173 firings)
        'kes',
        # scot  (167 firings)
        ' Scots',
        # bee  (167 firings)
        ' bees', ' Bees',
        # gaz  (164 firings)
        ' Gaz',
        # mourn  (164 firings)
        ' mourn',
        # slur  (158 firings)
        ' slur', ' slurs',
        # counselor  (145 firings)
        ' counselor', ' counselors',
        # ace  (144 firings)
        ' Ace',
        # que  (143 firings)
        ' queer',
        # cage  (137 firings)
        ' Cage',
        # claw  (133 firings)
        ' claw', ' Claw',
        # jung  (130 firings)
        ' Jung',
        # cran  (129 firings)
        ' Cran', ' cran',
        # kang  (128 firings)
        ' Kang',
        # cobb  (123 firings)
        ' Cobb',
        # swan  (123 firings)
        ' Swan',
        # crowley  (118 firings)
        ' Crowley',
        # scrub  (115 firings)
        ' scrub',
        # journey  (114 firings)
        ' Journey',
        # blu  (110 firings)
        ' blues',
        # pike  (107 firings)
        ' Pike',
        # roku  (101 firings)
        ' Roku',
        # kem  (100 firings)
        ' Kem',
        # shel  (97 firings)
        ' Shel',
        # cay  (96 firings)
        ' Cay',
        # dwell  (96 firings)
        ' dwell',
        # slack  (94 firings)
        ' Slack',
        # cock  (93 firings)
        ' Cock',
        # bun  (92 firings)
        ' Bun',
        # segrega  (91 firings)
        ' segregation',
        # daniel  (91 firings)
        ' Daniels',
        # discriminatory  (91 firings)
        ' discriminatory',
        # nun  (90 firings)
        ' Nun',
        # wrest  (88 firings)
        ' wrest',
        # norse  (81 firings)
        ' Norse',
        # bon  (80 firings)
        ' Bones',
        # cary  (80 firings)
        ' Cary',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'hawk-family', 1

def prog_L06F21940(input_tokens):
    """19 token families, 23 surface forms (train F1 of the uncapped optimum: 0.370).
    Fires at 69,559 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: names of football players and related statistics"""
    # --- end external annotation ---
    fire = {
        # city  (766 firings)
        ' City',
        # scor  (496 firings)
        ' scored', ' scoring', ' scorer',
        # strik  (347 firings)
        ' striker', ' strikers',
        # mourinho  (325 firings)
        ' Mourinho',
        # ane  (313 firings)
        'ane',
        # midfield  (311 firings)
        ' midfielder', ' midfield',
        # rodg  (283 firings)
        ' Rodgers',
        # ini  (264 firings)
        'ini',
        # ovic  (241 firings)
        'ovic',
        # ba  (203 firings)
        'ba',
        # silva  (200 firings)
        ' Silva',
        # weng  (200 firings)
        ' Wenger',
        # gaal  (199 firings)
        ' Gaal',
        # klopp  (189 firings)
        ' Klopp',
        # ronaldo  (186 firings)
        ' Ronaldo',
        # rooney  (184 firings)
        ' Rooney',
        # kane  (184 firings)
        ' Kane',
        # messi  (183 firings)
        ' Messi',
        # brady  (178 firings)
        ' Brady',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'city-family', 1

def prog_L06F21941(input_tokens):
    """44 token families, 53 surface forms (train F1 of the uncapped optimum: 0.558).
    Fires at 12,659 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: mentions of transcripts"""
    # --- end external annotation ---
    fire = {
        # transcript  (750 firings)
        ' transcript', ' Transcript', ' transcripts',
        # audio  (530 firings)
        ' audio', 'Audio',
        # text  (445 firings)
        ' text',
        # excerpt  (396 firings)
        ' excerpt', ' excerpts',
        # cript  (218 firings)
        'cript',
        # minut  (201 firings)
        ' Minutes',
        # copy  (164 firings)
        ' Copy',
        # record  (152 firings)
        ' recordings',
        # transc  (140 firings)
        ' transc',
        # tap  (132 firings)
        ' tapes',
        # replay  (128 firings)
        ' replay',
        # entirety  (123 firings)
        ' entirety',
        # proceed  (117 firings)
        ' Proceedings',
        # purse  (117 firings)
        ' purse',
        # rubin  (115 firings)
        ' Rubin',
        # snippet  (111 firings)
        ' snippet', ' snippets',
        # chomsky  (107 firings)
        ' Chomsky',
        # clip  (96 firings)
        ' clips',
        # cerpt  (95 firings)
        'cerpt',
        # screenshot  (91 firings)
        'Screenshot',
        # brend  (84 firings)
        'Brend',
        # dialect  (73 firings)
        ' dialect',
        # acket  (73 firings)
        'acket', 'ackets',
        # ript  (68 firings)
        'ript', 'RIPT',
        # aloud  (67 firings)
        ' aloud',
        # overheard  (66 firings)
        ' overheard',
        # syll  (66 firings)
        ' syll',
        # receipt  (66 firings)
        ' receipts',
        # redact  (65 firings)
        ' redacted',
        # qur  (63 firings)
        ' Qur',
        # video  (63 firings)
        ' VIDEO',
        # subtitl  (62 firings)
        ' subtitles',
        # paraph  (61 firings)
        ' paraph',
        # cita  (61 firings)
        ' citation', ' Citation',
        # reen  (59 firings)
        'reen',
        # transcrip  (48 firings)
        ' transcription',
        # narrator  (47 firings)
        ' narrator',
        # corpu  (44 firings)
        ' corpus', ' Corpus',
        # brenda  (43 firings)
        ' Brenda',
        # subtitle  (41 firings)
        ' subtitle',
        # condens  (41 firings)
        ' condensed',
        # citation  (40 firings)
        ' citations',
        # plo  (35 firings)
        ' PLoS',
        # phon  (34 firings)
        ' phon',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'transcript-family', 1

def prog_L06F21942(input_tokens):
    """34 token families, 35 surface forms (train F1 of the uncapped optimum: 0.287).
    Fires at 36,083 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to various government departments and their functions"""
    # --- end external annotation ---
    fire = {
        # health  (533 firings)
        ' Health',
        # justice  (421 firings)
        ' Justice',
        # human  (418 firings)
        ' Human',
        # homeland  (380 firings)
        ' Homeland',
        # publ  (357 firings)
        ' Public',
        # control  (314 firings)
        ' Control',
        # affair  (304 firings)
        ' Affairs',
        # educa  (289 firings)
        ' Education',
        # transporta  (285 firings)
        ' Transportation',
        # energy  (273 firings)
        ' Energy',
        # immigra  (252 firings)
        ' Immigration',
        # foreign  (252 firings)
        ' Foreign',
        # environment  (229 firings)
        ' Environmental',
        # disease  (225 firings)
        ' Disease',
        # labor  (206 firings)
        ' Labor',
        # econom  (197 firings)
        ' Economic',
        # environ  (191 firings)
        ' Environment', 'Environment',
        # revenue  (189 firings)
        ' Revenue',
        # agriculture  (186 firings)
        ' Agriculture',
        # trade  (170 firings)
        ' Trade',
        # custom  (162 firings)
        ' Customs',
        # appeal  (162 firings)
        ' Appeals',
        # manage  (159 firings)
        ' Management',
        # natur  (148 firings)
        ' Natural',
        # statistic  (127 firings)
        ' Statistics',
        # investiga  (122 firings)
        ' Investigation',
        # resourc  (121 firings)
        ' Resources',
        # rex  (118 firings)
        ' Rex',
        # bord  (118 firings)
        ' Border',
        # medicine  (116 firings)
        ' Medicine',
        # commerce  (112 firings)
        ' Commerce',
        # veteran  (106 firings)
        ' Veterans',
        # interior  (103 firings)
        ' Interior',
        # hous  (97 firings)
        ' Housing',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'health-family', 1

def prog_L06F21943(input_tokens):
    """7 token families, 22 surface forms (train F1 of the uncapped optimum: 0.119).
    Fires at 615,406 of 36,786,566 positions.
    Fires at 1.67% of positions, and
    token rules do not serve features this dense: median test F1 0.086
    across the 37,173 features above 0.39% of positions, against 0.763 for
    the 76,283 below 0.016%. Read this fire set as the best available
    approximation, not as what the feature does."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: technical terms and concepts relevant to programming and technology"""
    # --- end external annotation ---
    fire = {
        # �  (33,182 firings)
        '�', ' �',
        # )  (3,170 firings)
        ')',
        # m  (2,799 firings)
        'm', 'M', ' M', ' m',
        # c  (2,372 firings)
        'C', ' C', 'c', ' c',
        # a  (1,930 firings)
        ' A', 'a', 'ía',
        # b  (1,672 firings)
        ' B', 'B', 'b', ' b',
        # d  (1,601 firings)
        'D', 'd', ' d', ' dé',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return '�-family', 1

def prog_L06F21944(input_tokens):
    """7 token families, 22 surface forms (train F1 of the uncapped optimum: 0.161).
    Fires at 518,135 of 36,786,566 positions.
    Fires at 1.41% of positions, and
    token rules do not serve features this dense: median test F1 0.086
    across the 37,173 features above 0.39% of positions, against 0.763 for
    the 76,283 below 0.016%. Read this fire set as the best available
    approximation, not as what the feature does."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: terms related to formal documents and structures"""
    # --- end external annotation ---
    fire = {
        # -  (21,011 firings)
        '-',
        # new  (5,196 firings)
        ' new', ' news', ' newly', 'new', ' newer',
        # year  (2,276 firings)
        'year', ' yearly',
        # old  (1,681 firings)
        'old', ' old', 'olding',
        # high  (1,679 firings)
        ' high', ' higher', ' highly', 'high', 'highly',
        # state  (1,593 firings)
        ' statement', 'state', 'statement',
        # long  (1,442 firings)
        ' long', 'long', ' LONG',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return '--family', 1

def prog_L06F21945(input_tokens):
    """47 token families, 62 surface forms (train F1 of the uncapped optimum: 0.689).
    Fires at 24,865 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to backpacks and their related contexts"""
    # --- end external annotation ---
    fire = {
        # pack  (400 firings)
        'pack', 'packs', 'packing', ' Packs',
        # hik  (397 firings)
        ' hiking', ' hikes', ' hikers',
        # hike  (327 firings)
        ' hike',
        # ?!  (292 firings)
        '?!',
        # monk  (289 firings)
        ' monk', ' monks', ' Monk',
        # n  (265 firings)
        'án',
        # refuge  (248 firings)
        ' refuge', ' Refuge', ' Refugees',
        # tra  (242 firings)
        ' Tra',
        # kaepernick  (241 firings)
        ' Kaepernick',
        # itive  (227 firings)
        'itive',
        # hq  (223 firings)
        ' HQ', 'HQ',
        # tf  (223 firings)
        'TF', ' TF', 'tf',
        # backpack  (221 firings)
        ' backpack',
        # iman  (198 firings)
        'iman',
        # itarian  (192 firings)
        'itarian',
        # wal  (187 firings)
        'Wal',
        # hamburg  (179 firings)
        ' Hamburg',
        # stefan  (172 firings)
        ' Stefan',
        # rio  (171 firings)
        'rio',
        # ban  (165 firings)
        'ban',
        # ulk  (158 firings)
        'ulk',
        # squat  (154 firings)
        ' squat', ' squats',
        # ord  (153 firings)
        ' Ord',
        # hut  (151 firings)
        ' Hut', ' hut',
        # hulk  (149 firings)
        ' Hulk',
        # riot  (148 firings)
        ' Riot',
        # jeep  (141 firings)
        ' Jeep',
        # bundy  (139 firings)
        ' Bundy',
        # undraft  (122 firings)
        ' undrafted',
        # ricardo  (121 firings)
        ' Ricardo',
        # bund  (118 firings)
        ' Bund',
        # summ  (114 firings)
        ' summ', ' summed',
        # dunn  (112 firings)
        ' Dunn',
        # fugit  (109 firings)
        ' fugitive',
        # jorge  (109 firings)
        ' Jorge',
        # johnston  (109 firings)
        ' Johnston',
        # uchin  (107 firings)
        'uchin',
        # ampa  (106 firings)
        'ampa',
        # stad  (105 firings)
        'stad',
        # detain  (103 firings)
        ' detain',
        # jiang  (103 firings)
        'jiang',
        # doub  (100 firings)
        ' doub',
        # huff  (99 firings)
        ' Huff',
        # tall  (98 firings)
        'tall',
        # stadt  (97 firings)
        'stadt',
        # ouf  (97 firings)
        'ouf',
        # fast  (94 firings)
        ' fasting',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'pack-family', 1

def prog_L06F21946(input_tokens):
    """39 token families, 56 surface forms (train F1 of the uncapped optimum: 0.635).
    Fires at 19,254 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: instances of the word "praise" and its variations"""
    # --- end external annotation ---
    fire = {
        # celebrat  (1,176 firings)
        ' celebrated', ' celebrating', ' celebrates',
        # critic  (1,098 firings)
        ' criticized', ' criticised',
        # pra  (576 firings)
        ' praised', ' Pra',
        # praise  (487 firings)
        ' praise',
        # defend  (388 firings)
        ' defended', ' defends',
        # hail  (351 firings)
        ' hailed',
        # tout  (326 firings)
        ' touted', ' touting',
        # welcom  (290 firings)
        ' welcomed',
        # endors  (289 firings)
        ' endorsed', ' endorsing',
        # criticiz  (264 firings)
        ' criticizing',
        # thank  (263 firings)
        ' thanked', ' thanking',
        # mock  (258 firings)
        ' mocked', ' mocking',
        # credit  (253 firings)
        ' credited',
        # prais  (239 firings)
        ' praising', ' praises',
        # applaud  (201 firings)
        ' applaud', ' applauded',
        # laud  (200 firings)
        ' lauded', ' laud',
        # tribute  (196 firings)
        ' tribute',
        # honor  (195 firings)
        ' honored', ' honoring',
        # cheer  (187 firings)
        ' cheered', ' cheering',
        # criticize  (168 firings)
        ' criticize',
        # compli  (156 firings)
        ' compliment', ' compliments',
        # approv  (147 firings)
        ' approving', ' approves',
        # glow  (142 firings)
        ' glowing',
        # reward  (141 firings)
        ' rewarded',
        # admire  (133 firings)
        ' admire',
        # admir  (133 firings)
        ' admired', ' admirable',
        # condemn  (119 firings)
        ' condemning',
        # salute  (103 firings)
        ' salute',
        # accol  (97 firings)
        ' accol',
        # honorary  (95 firings)
        ' honorary',
        # glor  (91 firings)
        ' glor',
        # admira  (82 firings)
        ' admiration',
        # congratulat  (80 firings)
        ' congratulated',
        # retweet  (80 firings)
        ' retweet',
        # lament  (78 firings)
        ' lamented',
        # congratulate  (76 firings)
        ' congratulate',
        # congrat  (74 firings)
        ' congrat',
        # complimentary  (59 firings)
        ' complimentary',
        # commend  (57 firings)
        ' commend',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'celebrat-family', 1

def prog_L06F21947(input_tokens):
    """37 token families, 47 surface forms (train F1 of the uncapped optimum: 0.676).
    Fires at 12,629 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to bicycles and biking"""
    # --- end external annotation ---
    fire = {
        # bike  (1,924 firings)
        ' bike', ' Bike', 'bike',
        # bicycle  (563 firings)
        ' bicycle', ' Bicycle',
        # bik  (501 firings)
        ' bikes', ' biking',
        # cycl  (451 firings)
        ' cycling', 'cycl', 'cycles',
        # motorcycle  (391 firings)
        ' motorcycle',
        # cyclist  (334 firings)
        ' cyclists',
        # bicycl  (236 firings)
        ' bicycles', ' bicycl',
        # wheel  (216 firings)
        ' wheels',
        # ike  (159 firings)
        'ikes',
        # patel  (139 firings)
        ' Patel',
        # pistol  (129 firings)
        ' pistol',
        # cycle  (129 firings)
        'cycle', ' Cycle',
        # harley  (127 firings)
        ' Harley',
        # puppy  (115 firings)
        ' puppy',
        # cruis  (114 firings)
        ' cruiser', ' Cruiser',
        # motorcycl  (112 firings)
        ' motorcycles',
        # ped  (108 firings)
        ' pedal',
        # oot  (105 firings)
        'ooter', 'ooters',
        # soda  (97 firings)
        ' soda',
        # cigarette  (97 firings)
        ' cigarette',
        # bm  (85 firings)
        ' BM',
        # thumb  (85 firings)
        ' thumbs',
        # shim  (83 firings)
        ' Shim',
        # iker  (77 firings)
        'ikers',
        # goat  (75 firings)
        ' goats',
        # asaki  (64 firings)
        'asaki',
        # bip  (58 firings)
        ' bip',
        # bi  (52 firings)
        ' BI',
        # stationary  (47 firings)
        ' stationary',
        # bicy  (45 firings)
        ' bicy',
        # cane  (45 firings)
        ' cane',
        # tractor  (44 firings)
        ' tractor',
        # icycle  (42 firings)
        'icycle',
        # pedal  (41 firings)
        ' pedals',
        # cabbage  (40 firings)
        ' cabbage',
        # lightsab  (34 firings)
        ' lightsaber',
        # blade  (34 firings)
        'blade',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'bike-family', 1

def prog_L06F21948(input_tokens):
    """12 token families, 20 surface forms (train F1 of the uncapped optimum: 0.794).
    Fires at 5,760 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: occurrences of the word "double" """
    # --- end external annotation ---
    fire = {
        # double  (2,316 firings)
        ' double', ' Double', 'double', 'Double',
        # triple  (682 firings)
        ' triple', ' Triple',
        # doubl  (592 firings)
        ' doubled', ' doubles', ' doubling',
        # single  (182 firings)
        ' Single', 'Single', 'single',
        # doub  (82 firings)
        ' doub',
        # cros  (60 firings)
        'Cross',
        # shortcut  (35 firings)
        ' shortcut',
        # brute  (30 firings)
        ' brute',
        # shift  (28 firings)
        ' Shift',
        # duplicate  (26 firings)
        ' duplicate',
        # ble  (24 firings)
        'BLE',
        # ouble  (15 firings)
        'ouble',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'double-family', 1

def prog_L06F21949(input_tokens):
    """3 token families, 10 surface forms (train F1 of the uncapped optimum: 0.723).
    Fires at 26,798 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to individuals in leadership positions or titles"""
    # --- end external annotation ---
    fire = {
        # president  (20,182 firings)
        ' President', ' president', 'President', 'president', ' presidents', ' Presidents', ' PRESIDENT',
        # vp  (295 firings)
        ' VP', 'VP',
        # treasur  (67 firings)
        ' treasurer',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'president-family', 1

def prog_L06F21950(input_tokens):
    """12 token families, 21 surface forms (train F1 of the uncapped optimum: 0.068).
    Fires at 233,260 of 36,786,566 positions.
    Fires at 0.63% of positions, and
    token rules do not serve features this dense: median test F1 0.086
    across the 37,173 features above 0.39% of positions, against 0.763 for
    the 76,283 below 0.016%. Read this fire set as the best available
    approximation, not as what the feature does."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: occurrences of personal pronouns and indicators of collective experiences or actions"""
    # --- end external annotation ---
    fire = {
        # the  (4,743 firings)
        'The',
        # new  (2,037 firings)
        ' new', 'NEW', ' NEW',
        # said  (1,893 firings)
        ' said',
        # say  (1,607 firings)
        ' say', ' says',
        # a  (1,581 firings)
        'A',
        # can  (1,547 firings)
        ' can', ' Can', 'CAN',
        # we  (1,117 firings)
        ' We', 'We',
        # could  (880 firings)
        ' could',
        # but  (838 firings)
        'But',
        # man  (703 firings)
        ' man', ' MAN',
        # help  (688 firings)
        ' help', ' helped', ' helping',
        # --  (628 firings)
        ' --',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'the-family', 1

def prog_L06F21951(input_tokens):
    """8 token families, 28 surface forms (train F1 of the uncapped optimum: 0.206).
    Fires at 400,591 of 36,786,566 positions.
    Fires at 1.09% of positions, and
    token rules do not serve features this dense: median test F1 0.086
    across the 37,173 features above 0.39% of positions, against 0.763 for
    the 76,283 below 0.016%. Read this fire set as the best available
    approximation, not as what the feature does."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to notable films and cultural icons, particularly in contexts involving tragedy or social commentary"""
    # --- end external annotation ---
    fire = {
        # trump  (2,820 firings)
        ' Trump', 'Trump',
        # war  (2,162 firings)
        ' War', ' war', ' Wars', 'war', ' wars', 'Wars', ' WAR',
        # obama  (1,720 firings)
        ' Obama',
        # car  (1,640 firings)
        ' car', ' cars', 'car', ' Cars', 'cars',
        # school  (1,566 firings)
        ' school', ' schools', ' School', 'school', ' Schools', ' schooling',
        # elec  (1,214 firings)
        ' election', 'election', ' Election',
        # world  (1,198 firings)
        ' world',
        # children  (1,176 firings)
        ' children', ' Children', 'children',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'trump-family', 1

def prog_L06F21952(input_tokens):
    """5 token families, 5 surface forms (train F1 of the uncapped optimum: 0.486).
    Fires at 15,699 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: instances of the word "I" and look for an empty document identifier"""
    # --- end external annotation ---
    fire = {
        # i  (11,750 firings)
        'I',
        # ii  (143 firings)
        'II',
        # ipa  (129 firings)
        ' IPA',
        # ai  (114 firings)
        'AI',
        # ari  (54 firings)
        'ARI',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'i-family', 1

def prog_L06F21953(input_tokens):
    """48 token families, 62 surface forms (train F1 of the uncapped optimum: 0.699).
    Fires at 20,104 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: the word "Has" along with variations of the term "bro." """
    # --- end external annotation ---
    fire = {
        # has  (1,455 firings)
        ' Has', 'has', 'Has', ' HAS',
        # bro  (397 firings)
        'bro',
        # had  (259 firings)
        ' Had',
        # junior  (257 firings)
        ' Junior',
        # expo  (243 firings)
        ' Expo',
        # icon  (236 firings)
        'icon', 'icons',
        # tes  (216 firings)
        ' Tes', 'tes', 'Tes',
        # ardo  (207 firings)
        'ardo',
        # crossov  (197 firings)
        ' crossover',
        # tro  (197 firings)
        'tro', 'Tro',
        # lego  (188 firings)
        ' LEGO',
        # ces  (175 firings)
        ' CES',
        # transform  (174 firings)
        ' Transformers', 'Transform',
        # devin  (173 firings)
        ' Devin',
        # yosh  (155 firings)
        ' Yosh',
        # produ  (152 firings)
        'produ', ' Produ',
        # ibo  (151 firings)
        'ibo',
        # hath  (134 firings)
        ' Hath', ' hath',
        # eb  (133 firings)
        ' Eb', ' EB',
        # hodg  (128 firings)
        ' Hodg',
        # veh  (127 firings)
        'veh', 'Veh', ' veh',
        # mes  (125 firings)
        ' Mes',
        # turbo  (125 firings)
        ' turbo', ' Turbo',
        # nun  (123 firings)
        ' Nunes',
        # jal  (119 firings)
        ' Jal',
        # eid  (109 firings)
        ' Eid',
        # harmon  (109 firings)
        ' Harmon',
        # hib  (108 firings)
        'hib',
        # toy  (104 firings)
        ' Toys',
        # abram  (104 firings)
        ' Abrams',
        # defy  (102 firings)
        ' defy',
        # def  (102 firings)
        ' defied',
        # comm  (99 firings)
        'comm',
        # wayne  (95 firings)
        'wayne',
        # appl  (93 firings)
        ' Applied',
        # xavi  (89 firings)
        ' Xavier',
        # idlib  (89 firings)
        ' Idlib',
        # cis  (88 firings)
        ' cis',
        # unc  (88 firings)
        ' Unc',
        # esc  (88 firings)
        ' escal',
        # bac  (84 firings)
        ' Bac',
        # igen  (83 firings)
        'igen',
        # endor  (83 firings)
        'endor',
        # rex  (82 firings)
        'rex',
        # jav  (77 firings)
        ' Jav',
        # cir  (75 firings)
        ' Cir',
        # hobby  (70 firings)
        ' Hobby',
        # gau  (69 firings)
        ' Gau',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'has-family', 1

def prog_L06F21954(input_tokens):
    """2 token families, 3 surface forms (train F1 of the uncapped optimum: 0.093).
    Fires at 48,343 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to deaths or incidents involving individuals"""
    # --- end external annotation ---
    fire = {
        # of  (35,841 firings)
        ' of', ' Of',
        # kill  (337 firings)
        ' killed',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'of-family', 1

def prog_L06F21955(input_tokens):
    """8 token families, 12 surface forms (train F1 of the uncapped optimum: 0.802).
    Fires at 9,316 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: mentions of "Internet." """
    # --- end external annotation ---
    fire = {
        # internet  (6,084 firings)
        ' Internet', ' internet', 'Internet', 'internet',
        # net  (346 firings)
        ' Net',
        # iot  (160 firings)
        ' IoT',
        # aid  (143 firings)
        ' AIDS',
        # offline  (110 firings)
        'Offline',
        # arcade  (87 firings)
        ' Arcade',
        # unix  (73 firings)
        ' Unix', 'Unix',
        # network  (29 firings)
        'Network',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'internet-family', 1

def prog_L06F21956(input_tokens):
    """1 token families, 1 surface forms (train F1 of the uncapped optimum: 0.272).
    Fires at 111,430 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: instances of the word "to" """
    # --- end external annotation ---
    fire = {
        # to  (108,954 firings)
        ' to',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'to-family', 1

def prog_L06F21957(input_tokens):
    """44 token families, 54 surface forms (train F1 of the uncapped optimum: 0.631).
    Fires at 8,066 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: terms related to torrenting and file-sharing"""
    # --- end external annotation ---
    fire = {
        # torrent  (619 firings)
        ' torrent', 'Torrent', ' Torrent',
        # rent  (260 firings)
        'rent', ' Rent',
        # fin  (242 firings)
        ' fin',
        # tor  (222 firings)
        'tor',
        # pir  (174 firings)
        ' pir', ' Pir',
        # track  (173 firings)
        ' tracker', ' Tracker', 'Tracker',
        # allan  (158 firings)
        ' Allan',
        # extradi  (146 firings)
        ' extradition',
        # download  (120 firings)
        ' downloads',
        # rainfall  (116 firings)
        ' rainfall',
        # [/  (112 firings)
        '[/', ' [/',
        # clamp  (109 firings)
        ' clamp',
        # dropbox  (108 firings)
        ' Dropbox',
        # fugit  (101 firings)
        ' fugitive',
        # vinyl  (101 firings)
        ' vinyl',
        # album  (98 firings)
        ' Album',
        # pload  (89 firings)
        'pload',
        # abyt  (83 firings)
        'abytes',
        # takedown  (81 firings)
        ' takedown',
        # extrad  (78 firings)
        ' extrad',
        # rar  (77 firings)
        'rar',
        # dmca  (69 firings)
        ' DMCA',
        # franoi  (68 firings)
        ' François',
        # boyle  (65 firings)
        ' Boyle',
        # mbp  (62 firings)
        'Mbps',
        # disconnect  (61 firings)
        ' disconnect',
        # hud  (44 firings)
        ' Hud',
        # uri  (44 firings)
        ' Uri', ' URI',
        # diff  (43 firings)
        ' diff',
        # regist  (42 firings)
        ' regist',
        # asar  (42 firings)
        'asar',
        # fug  (41 firings)
        ' fug',
        # antiv  (40 firings)
        ' antiv',
        # ansom  (37 firings)
        'ansom',
        # eth  (36 firings)
        ' ether',
        # orr  (33 firings)
        'orr',
        # aval  (31 firings)
        ' Aval',
        # depr  (30 firings)
        ' deprive',
        # anonym  (30 firings)
        ' anonym',
        # mpeg  (27 firings)
        ' MPEG', 'mpeg',
        # depri  (26 firings)
        ' depri',
        # thumbnail  (25 firings)
        ' thumbnail',
        # attach  (24 firings)
        ' attachments', 'Attach',
        # radiator  (21 firings)
        ' radiator',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'torrent-family', 1

def prog_L06F21958(input_tokens):
    """8 token families, 9 surface forms (train F1 of the uncapped optimum: 0.193).
    Fires at 153,782 of 36,786,566 positions.
    Fires at 0.42% of positions, and
    token rules do not serve features this dense: median test F1 0.086
    across the 37,173 features above 0.39% of positions, against 0.763 for
    the 76,283 below 0.016%. Read this fire set as the best available
    approximation, not as what the feature does."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: names of individuals involved in controversy or conflict"""
    # --- end external annotation ---
    fire = {
        # trump  (4,961 firings)
        ' Trump',
        # mr  (1,687 firings)
        ' Mr',
        # clinton  (1,398 firings)
        ' Clinton',
        # obama  (1,167 firings)
        ' Obama',
        # j  (513 firings)
        'j',
        # sand  (485 firings)
        ' Sanders',
        # paul  (467 firings)
        ' Paul',
        # jon  (463 firings)
        ' Jones', 'Jones',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'trump-family', 1

def prog_L06F21959(input_tokens):
    """12 token families, 22 surface forms (train F1 of the uncapped optimum: 0.165).
    Fires at 341,408 of 36,786,566 positions.
    Fires at 0.93% of positions, and
    token rules do not serve features this dense: median test F1 0.086
    across the 37,173 features above 0.39% of positions, against 0.763 for
    the 76,283 below 0.016%. Read this fire set as the best available
    approximation, not as what the feature does."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: phrases related to legal accusations and intentionality"""
    # --- end external annotation ---
    fire = {
        # -  (35,430 firings)
        '-',
        # �  (9,544 firings)
        ' �',
        # t  (6,031 firings)
        't', 'ét',
        # re  (2,673 firings)
        're',
        # very  (1,926 firings)
        ' very', 'very', ' VERY',
        # and  (1,286 firings)
        'and',
        # far  (1,149 firings)
        ' far', 'far',
        # edit  (1,103 firings)
        ' edit', ' edited',
        # un  (983 firings)
        ' un', 'un',
        # ly  (976 firings)
        'ly',
        # quite  (968 firings)
        ' quite', 'quite', 'Quite', ' Quite',
        # c  (920 firings)
        'c', ' c',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return '--family', 1

def prog_L06F21960(input_tokens):
    """4 token families, 8 surface forms (train F1 of the uncapped optimum: 0.268).
    Fires at 12,856 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: the phrase "something else." """
    # --- end external annotation ---
    fire = {
        # else  (1,785 firings)
        ' else', ' Else', 'else', 'Else',
        # elsewhere  (307 firings)
        ' elsewhere',
        # otherwise  (176 firings)
        ' otherwise',
        # oth  (154 firings)
        'other', 'OTHER',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'else-family', 1

def prog_L06F21961(input_tokens):
    """5 token families, 5 surface forms (train F1 of the uncapped optimum: 0.044).
    Fires at 24,887 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: phrases related to sentencing and prison terms"""
    # --- end external annotation ---
    fire = {
        # to  (15,299 firings)
        ' to',
        # fac  (134 firings)
        ' faces',
        # worth  (86 firings)
        ' worth',
        # suspend  (73 firings)
        ' suspended',
        # prison  (69 firings)
        ' prison',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'to-family', 1

def prog_L06F21962(input_tokens):
    """36 token families, 45 surface forms (train F1 of the uncapped optimum: 0.778).
    Fires at 6,547 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to Mars and related terms"""
    # --- end external annotation ---
    fire = {
        # mar  (1,458 firings)
        ' Mars', ' MAR', 'Mars', ' mars',
        # lunar  (285 firings)
        ' lunar', ' Lunar',
        # rov  (232 firings)
        ' rover',
        # planetary  (211 firings)
        ' planetary', ' Planetary',
        # planet  (182 firings)
        ' planets',
        # martian  (170 firings)
        ' Martian',
        # mast  (170 firings)
        ' Mast', ' mast', 'mast',
        # rail  (165 firings)
        ' Rails',
        # venu  (164 firings)
        ' Venus',
        # curios  (146 firings)
        ' Curiosity',
        # antarctica  (113 firings)
        ' Antarctica',
        # microb  (105 firings)
        ' microbial', ' microbes',
        # iss  (100 firings)
        ' ISS',
        # surpas  (100 firings)
        ' surpass',
        # extrat  (99 firings)
        ' extrater',
        # deport  (84 firings)
        ' deport',
        # oplan  (81 firings)
        'oplan',
        # terra  (80 firings)
        ' Terra',
        # sclerosi  (77 firings)
        ' sclerosis',
        # maco  (70 firings)
        ' macOS',
        # stem  (62 firings)
        ' STEM', 'STEM',
        # prost  (56 firings)
        ' prost',
        # deu  (55 firings)
        ' Deus',
        # mri  (55 firings)
        'MRI',
        # microbiome  (46 firings)
        ' microbiome',
        # aration  (45 firings)
        'arations',
        # als  (40 firings)
        ' ALS',
        # cer  (39 firings)
        ' Ceres',
        # aru  (38 firings)
        'arus',
        # mare  (36 firings)
        ' Mare',
        # rem  (32 firings)
        ' remed',
        # gres  (32 firings)
        'gress',
        # petra  (29 firings)
        ' Petra',
        # kush  (27 firings)
        ' Kush',
        # metast  (22 firings)
        ' metast',
        # are  (21 firings)
        ' Ares',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'mar-family', 1

def prog_L06F21963(input_tokens):
    """49 token families, 55 surface forms (train F1 of the uncapped optimum: 0.681).
    Fires at 9,915 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: occurrences of the word "na" and its variations, suggesting a focus on phrases that describe a state or condition"""
    # --- end external annotation ---
    fire = {
        # na  (257 firings)
        ' na', 'Na',
        # bu  (162 firings)
        ' bu',
        # para  (155 firings)
        ' para', ' paras',
        # ya  (155 firings)
        ' ya', ' Ya',
        # opa  (148 firings)
        'opa',
        # bel  (146 firings)
        ' belly',
        # olla  (144 firings)
        'olla',
        # aney  (139 firings)
        'aney',
        # mas  (135 firings)
        ' mas',
        # naw  (131 firings)
        ' Naw',
        # mi  (131 firings)
        ' mi',
        # ana  (128 firings)
        ' Ana', ' ana',
        # ra  (117 firings)
        ' ra',
        # brennan  (114 firings)
        ' Brennan',
        # sta  (111 firings)
        'sta', ' STA',
        # pa  (104 firings)
        ' pa',
        # oca  (103 firings)
        'oca',
        # osta  (102 firings)
        'osta',
        # enei  (100 firings)
        'enei',
        # navajo  (95 firings)
        ' Navajo',
        # pil  (91 firings)
        ' pil',
        # opera  (91 firings)
        ' Opera',
        # nou  (86 firings)
        ' Nou',
        # underpin  (83 firings)
        ' underpin',
        # loch  (80 firings)
        ' Loch',
        # valid  (80 firings)
        ' validity',
        # ye  (77 firings)
        ' ye',
        # noon  (75 firings)
        ' Noon',
        # dat  (71 firings)
        ' dat',
        # ng  (68 firings)
        ' ng',
        # sana  (67 firings)
        ' Sana',
        # donn  (65 firings)
        ' Donn',
        # nah  (65 firings)
        ' Nah', 'nah',
        # powershell  (64 firings)
        ' PowerShell',
        # si  (64 firings)
        ' si',
        # aw  (61 firings)
        'Aw',
        # yo  (59 firings)
        ' yo',
        # ta  (58 firings)
        ' ta',
        # nas  (58 firings)
        ' Nass',
        # bek  (56 firings)
        'bek',
        # clo  (56 firings)
        ' clo',
        # decon  (55 firings)
        ' decon',
        # pier  (55 firings)
        ' pier',
        # sein  (53 firings)
        'sein',
        # tha  (52 firings)
        ' tha',
        # sop  (52 firings)
        ' Sop',
        # ajo  (48 firings)
        'ajo',
        # nay  (47 firings)
        ' Nay',
        # ni  (40 firings)
        ' ni',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'na-family', 1

def prog_L06F21964(input_tokens):
    """15 token families, 20 surface forms (train F1 of the uncapped optimum: 0.250).
    Fires at 107,577 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: proper nouns, specifically names of people"""
    # --- end external annotation ---
    fire = {
        # f  (547 firings)
        ' F',
        # g  (524 firings)
        ' G',
        # smith  (517 firings)
        ' Smith',
        # o  (486 firings)
        ' O',
        # brown  (452 firings)
        ' Brown',
        # e  (447 firings)
        ' E',
        # jon  (368 firings)
        ' Jones',
        # mc  (363 firings)
        ' Mc',
        # van  (353 firings)
        ' Van', ' van',
        # de  (350 firings)
        ' De',
        # mill  (344 firings)
        ' Miller', ' Mills', ' Mill',
        # william  (328 firings)
        ' Williams',
        # sch  (327 firings)
        ' Sch', ' SCH', ' Scher',
        # mcc  (308 firings)
        ' McC',
        # johnson  (281 firings)
        ' Johnson',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'f-family', 1

def prog_L06F21965(input_tokens):
    """45 token families, 59 surface forms (train F1 of the uncapped optimum: 0.643).
    Fires at 11,103 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to dietary supplements"""
    # --- end external annotation ---
    fire = {
        # supple  (319 firings)
        ' supplement', ' supplements', 'Supplement', ' Supplement',
        # suppl  (282 firings)
        ' supplies',
        # bolst  (243 firings)
        ' bolster',
        # expedi  (239 firings)
        ' expedition', ' Expedition',
        # capsule  (166 firings)
        ' capsule',
        # augment  (160 firings)
        ' augmented',
        # dop  (146 firings)
        ' doping',
        # dossi  (140 firings)
        ' dossier',
        # norton  (134 firings)
        ' Norton',
        # pill  (125 firings)
        ' pills',
        # reprint  (122 firings)
        ' reprinted', ' reprint',
        # nun  (121 firings)
        ' Nunes',
        # supplement  (121 firings)
        ' supplemental', ' Supplemental', ' supplemented',
        # ada  (113 firings)
        'ADA',
        # boost  (112 firings)
        ' booster', ' Booster', ' boosters',
        # steroid  (109 firings)
        ' steroids', ' steroid',
        # lement  (109 firings)
        'lements', 'lement',
        # patreon  (90 firings)
        ' Patreon',
        # berman  (89 firings)
        ' Berman',
        # omega  (87 firings)
        ' Omega',
        # swanson  (81 firings)
        ' Swanson',
        # tabletop  (81 firings)
        ' tabletop',
        # suzanne  (80 firings)
        ' Suzanne',
        # tc  (79 firings)
        ' TC',
        # etf  (79 firings)
        ' ETF', 'ETF',
        # sup  (77 firings)
        ' supers', ' SUP',
        # nutri  (68 firings)
        ' Nutrition', 'nutrition',
        # bolster  (67 firings)
        ' bolstered',
        # deficiency  (66 firings)
        ' deficiency',
        # phelp  (59 firings)
        ' Phelps',
        # olympia  (58 firings)
        ' Olympia',
        # adjunct  (57 firings)
        ' adjunct',
        # deficienc  (53 firings)
        ' deficiencies',
        # zinc  (53 firings)
        ' zinc',
        # defend  (53 firings)
        ' Defenders',
        # mushroom  (53 firings)
        ' mushroom',
        # rint  (51 firings)
        'rint',
        # endium  (49 firings)
        'endium',
        # aug  (49 firings)
        ' augment',
        # booklet  (49 firings)
        ' booklet',
        # powder  (44 firings)
        ' powdered',
        # reon  (43 firings)
        'reon',
        # iciency  (43 firings)
        'iciency',
        # stock  (43 firings)
        ' stocking',
        # garmin  (38 firings)
        ' Garmin',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'supple-family', 1

def prog_L06F21966(input_tokens):
    """11 token families, 42 surface forms (train F1 of the uncapped optimum: 0.153).
    Fires at 452,785 of 36,786,566 positions.
    Fires at 1.23% of positions, and
    token rules do not serve features this dense: median test F1 0.086
    across the 37,173 features above 0.39% of positions, against 0.763 for
    the 76,283 below 0.016%. Read this fire set as the best available
    approximation, not as what the feature does."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: legal terminology and concepts"""
    # --- end external annotation ---
    fire = {
        # to  (5,966 firings)
        ' to',
        # work  (2,714 firings)
        ' work', ' working', ' works', ' worked', 'work', 'working', 'works', ' workings', ' WORK', 'workers', 'worked',
        # it  (2,591 firings)
        ' it',
        # year  (2,437 firings)
        ' years', 'year', 'years', ' YEAR',
        # you  (2,091 firings)
        ' you',
        # time  (1,670 firings)
        ' time',
        # project  (1,520 firings)
        ' project', ' projects', ' Project', ' projected', 'project', ' Projects',
        # up  (1,492 firings)
        ' up',
        # people  (1,471 firings)
        ' people',
        # design  (1,138 firings)
        ' designed', ' design', ' designing', ' Design', ' designs', ' designer', 'designed', ' Designer', ' Designed',
        # charg  (1,133 firings)
        ' charges', ' charged', 'charged', ' charger', 'charges', 'Charges',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'to-family', 1

def prog_L06F21967(input_tokens):
    """7 token families, 17 surface forms (train F1 of the uncapped optimum: 0.070).
    Fires at 117,480 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to government and political themes"""
    # --- end external annotation ---
    fire = {
        # has  (3,097 firings)
        ' has',
        # said  (1,946 firings)
        ' said',
        # announc  (922 firings)
        ' announced', ' announces',
        # official  (737 firings)
        ' officials', ' officially',
        # govern  (632 firings)
        ' government', ' governments', 'Government', ' Governments', ' governs',
        # say  (516 firings)
        ' say', ' Says', ' Say',
        # offic  (382 firings)
        ' official', ' offices', 'official',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'has-family', 1

def prog_L06F21968(input_tokens):
    """45 token families, 51 surface forms (train F1 of the uncapped optimum: 0.618).
    Fires at 7,806 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: terms related to advisory roles and councils"""
    # --- end external annotation ---
    fire = {
        # advisory  (468 firings)
        ' advisory', ' Advisory',
        # consult  (238 firings)
        ' consulting', ' Consulting',
        # advisor  (164 firings)
        ' advisors', ' Advisor',
        # austrian  (163 firings)
        ' Austrian',
        # ogen  (139 firings)
        'ogenic',
        # important  (135 firings)
        ' Important', 'Important',
        # allison  (132 firings)
        ' Allison',
        # monica  (125 firings)
        ' Monica',
        # government  (110 firings)
        'governmental',
        # advi  (108 firings)
        ' Advis', ' advis',
        # therapeut  (107 firings)
        ' therapeutic',
        # ayan  (103 firings)
        'ayan',
        # aran  (102 firings)
        'aran',
        # accessory  (100 firings)
        ' accessory',
        # honorary  (96 firings)
        ' honorary',
        # advis  (91 firings)
        ' advising', ' advises',
        # oro  (80 firings)
        'oro',
        # solution  (79 firings)
        ' Solutions',
        # otive  (78 firings)
        'otive',
        # é  (77 firings)
        ' é',
        # ilater  (77 firings)
        'ilateral',
        # chair  (77 firings)
        ' chaired',
        # bulletin  (75 firings)
        ' bulletin',
        # erey  (65 firings)
        'erey',
        # eclect  (65 firings)
        ' eclectic',
        # informat  (63 firings)
        ' informative',
        # anian  (59 firings)
        'anian',
        # director  (57 firings)
        ' Directors',
        # authoritat  (54 firings)
        ' authoritative',
        # consultancy  (52 firings)
        ' consultancy',
        # inform  (51 firings)
        ' informational',
        # expert  (51 firings)
        ' Expert',
        # anic  (51 firings)
        'anical',
        # sandy  (49 firings)
        ' sandy',
        # visory  (48 firings)
        'visory',
        # ay  (48 firings)
        ' ay',
        # editor  (48 firings)
        ' Editorial',
        # bind  (47 firings)
        'binding',
        # agency  (46 firings)
        'agency',
        # minister  (45 firings)
        ' ministerial',
        # denise  (45 firings)
        ' Denise',
        # brokerage  (44 firings)
        ' brokerage',
        # discretionary  (44 firings)
        ' discretionary',
        # observ  (36 firings)
        ' observational',
        # instruction  (34 firings)
        ' instructional',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'advisory-family', 1

def prog_L06F21969(input_tokens):
    """45 token families, 63 surface forms (train F1 of the uncapped optimum: 0.644).
    Fires at 33,313 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: terms related to imaging and measurement technologies"""
    # --- end external annotation ---
    fire = {
        # ograph  (1,116 firings)
        'ographer', 'ograph', 'ographic', 'ographers', 'ographical', 'ographs', 'ographed', 'ographies',
        # ography  (644 firings)
        'ography',
        # omet  (301 firings)
        'ometer', 'ometers',
        # ocrat  (254 firings)
        'ocrat', 'ocrats', 'ocratic', 'ocrates',
        # ology  (227 firings)
        'ology',
        # osphere  (209 firings)
        'osphere',
        # ivity  (206 firings)
        'ivity',
        # oan  (198 firings)
        'oğan', 'oan',
        # ocese  (193 firings)
        'ocese',
        # olith  (191 firings)
        'olithic', 'olith',
        # ophobia  (187 firings)
        'ophobia',
        # ogram  (181 firings)
        'ogram', 'ograms',
        # imet  (165 firings)
        'imeter', 'imeters', 'imet',
        # ophob  (160 firings)
        'ophobic', 'ophob',
        # ozy  (144 firings)
        'ozy',
        # zuckerberg  (142 firings)
        ' Zuckerberg',
        # oha  (138 firings)
        'oha',
        # ive  (136 firings)
        'iveness',
        # owitz  (131 firings)
        'owitz',
        # ogen  (127 firings)
        'ogenic', 'ogenous',
        # otechnology  (126 firings)
        'otechnology',
        # atra  (126 firings)
        'atra',
        # athon  (124 firings)
        'athon',
        # ocracy  (123 firings)
        'ocracy',
        # rome  (123 firings)
        'rome',
        # exceptional  (116 firings)
        ' exceptionally',
        # utra  (116 firings)
        'utra',
        # osc  (115 firings)
        'osc',
        # awatt  (115 firings)
        'awatts',
        # plane  (115 firings)
        'plane',
        # posium  (113 firings)
        'posium',
        # abyt  (107 firings)
        'abytes',
        # orpg  (105 firings)
        'ORPG',
        # ophile  (104 firings)
        'ophile',
        # ron  (102 firings)
        'rones',
        # opia  (99 firings)
        'opia',
        # opo  (97 firings)
        'opoly',
        # oise  (97 firings)
        'oise',
        # atham  (94 firings)
        'atham',
        # obia  (92 firings)
        'obia',
        # eer  (90 firings)
        'eering',
        # orama  (90 firings)
        'orama',
        # screenplay  (89 firings)
        ' screenplay',
        # partisan  (89 firings)
        'partisan',
        # opathy  (88 firings)
        'opathy',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'ograph-family', 1

def prog_L06F21970(input_tokens):
    """25 token families, 31 surface forms (train F1 of the uncapped optimum: 0.740).
    Fires at 6,139 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to virtual reality environments and concepts"""
    # --- end external annotation ---
    fire = {
        # virtu  (1,949 firings)
        ' virtual', ' Virtual', 'Virtual', 'virtual',
        # ultimate  (377 firings)
        ' Ultimate', 'Ultimate',
        # sy  (196 firings)
        ' sy',
        # videog  (174 firings)
        ' videog',
        # augment  (170 firings)
        ' augmented',
        # immers  (97 firings)
        ' immersive',
        # holog  (87 firings)
        ' holog',
        # sam  (86 firings)
        ' sam',
        # vouch  (84 firings)
        ' vouchers', ' voucher',
        # kio  (82 firings)
        ' kios',
        # vag  (66 firings)
        ' Vag', 'vag',
        # hern  (65 firings)
        'hern',
        # vend  (60 firings)
        ' vending',
        # avatar  (50 firings)
        ' avatar',
        # simulat  (46 firings)
        ' simulated',
        # pav  (45 firings)
        ' pav',
        # omorph  (43 firings)
        'omorphic',
        # raph  (41 firings)
        'raphic',
        # lunar  (40 firings)
        ' Lunar',
        # atar  (38 firings)
        'atars',
        # bek  (34 firings)
        'bek',
        # virt  (33 firings)
        'virt',
        # phantom  (26 firings)
        ' phantom',
        # resent  (24 firings)
        'resent',
        # vik  (19 firings)
        'vik',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'virtu-family', 1

def prog_L06F21971(input_tokens):
    """15 token families, 34 surface forms (train F1 of the uncapped optimum: 0.226).
    Fires at 1,154,246 of 36,786,566 positions.
    Fires at 3.14% of positions, and
    token rules do not serve features this dense: median test F1 0.086
    across the 37,173 features above 0.39% of positions, against 0.763 for
    the 76,283 below 0.016%. Read this fire set as the best available
    approximation, not as what the feature does."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: newsworthy political events and discussions"""
    # --- end external annotation ---
    fire = {
        # a  (62,587 firings)
        ' a', 'A', ' A',
        # has  (27,045 firings)
        ' has',
        # aft  (13,120 firings)
        ' after',
        # have  (11,119 firings)
        ' have',
        # been  (11,068 firings)
        ' been',
        # week  (8,550 firings)
        ' week', ' weeks', 'week', ' Weeks',
        # year  (7,006 firings)
        ' year', ' years',
        # two  (6,424 firings)
        ' two', 'Two', ' Two',
        # new  (6,111 firings)
        ' new', ' newly', ' Newly',
        # month  (5,195 firings)
        ' month', ' months', 'month', ' Months',
        # over  (4,335 firings)
        ' over',
        # day  (3,838 firings)
        ' days', ' day', 'day', 'Days',
        # president  (3,333 firings)
        ' presidential', ' President',
        # washington  (3,300 firings)
        'WASHINGTON', ' Washington', 'Washington',
        # thursday  (3,104 firings)
        ' Thursday',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'a-family', 1

def prog_L06F21972(input_tokens):
    """16 token families, 23 surface forms (train F1 of the uncapped optimum: 0.769).
    Fires at 16,791 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: occurrences of the word "questions." """
    # --- end external annotation ---
    fire = {
        # question  (5,286 firings)
        ' questions', ' questioning', ' Questions', 'Questions',
        # ques  (4,995 firings)
        ' question', ' Question', 'Question', 'question',
        # wonder  (345 firings)
        ' wondering',
        # faq  (186 firings)
        ' FAQ', 'FAQ',
        # doubt  (162 firings)
        ' doubts',
        # quer  (143 firings)
        ' queries',
        # quiz  (141 firings)
        ' quiz',
        # inquir  (110 firings)
        ' inquiries',
        # quizz  (79 firings)
        ' quizz',
        # ama  (76 firings)
        ' AMA',
        # questionnaire  (73 firings)
        ' questionnaire',
        # inqu  (71 firings)
        ' inqu',
        # trivia  (69 firings)
        ' trivia',
        # interview  (63 firings)
        ' interviewer',
        # grassley  (51 firings)
        ' Grassley',
        # misconception  (50 firings)
        ' misconceptions',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'question-family', 1

def prog_L06F21973(input_tokens):
    """31 token families, 36 surface forms (train F1 of the uncapped optimum: 0.830).
    Fires at 5,811 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: instances of the term "crony" in various contexts related to economic and political critique"""
    # --- end external annotation ---
    fire = {
        # cr  (2,309 firings)
        ' cr', ' Cr', 'cr', 'Cr',
        # ec  (300 firings)
        ' Ec', ' ec',
        # crust  (177 firings)
        ' crust',
        # bryce  (136 firings)
        ' Bryce',
        # 2022  (125 firings)
        ' 2022',
        # cron  (122 firings)
        ' Cron',
        # crane  (105 firings)
        ' crane',
        # crank  (96 firings)
        ' crank',
        # ocr  (91 firings)
        'ocr',
        # rica  (91 firings)
        ' Rica',
        # cringe  (70 firings)
        ' cringe',
        # crat  (67 firings)
        ' crater',
        # bureaucr  (53 firings)
        ' bureaucr',
        # pseud  (51 firings)
        ' pseud',
        # circ  (50 firings)
        ' circ',
        # geh  (49 firings)
        ' Geh',
        # protr  (48 firings)
        ' protr',
        # overth  (48 firings)
        ' overth',
        # appar  (47 firings)
        ' appar',
        # desc  (46 firings)
        ' desc',
        # cradle  (43 firings)
        ' cradle',
        # extr  (43 firings)
        ' extr',
        # crumbl  (42 firings)
        ' crumbling',
        # pse  (37 firings)
        ' Pse', ' pse',
        # crumble  (36 firings)
        ' crumble',
        # ryce  (34 firings)
        'ryce',
        # occ  (34 firings)
        ' occ',
        # curl  (27 firings)
        ' curl',
        # eb  (24 firings)
        ' eb',
        # plast  (19 firings)
        ' plaster',
        # 236  (16 firings)
        ' 236',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'cr-family', 1

def prog_L06F21974(input_tokens):
    """46 token families, 55 surface forms (train F1 of the uncapped optimum: 0.721).
    Fires at 11,192 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to the term "sid" and its variations in context"""
    # --- end external annotation ---
    fire = {
        # sid  (468 firings)
        ' Sid', ' sid', 'sided', 'sid',
        # tayyip  (298 firings)
        ' Tayyip',
        # trad  (205 firings)
        ' Trad', ' trad',
        # tid  (191 firings)
        ' tid', ' Tid',
        # ped  (186 firings)
        ' Ped',
        # tyson  (165 firings)
        ' Tyson',
        # theft  (162 firings)
        ' Theft',
        # vind  (153 firings)
        'vind',
        # petty  (146 firings)
        ' petty', ' Petty',
        # sanford  (144 firings)
        ' Sanford',
        # background  (144 firings)
        'Background',
        # inda  (142 firings)
        'inda',
        # gavin  (135 firings)
        ' Gavin',
        # sidney  (129 firings)
        ' Sidney',
        # hardt  (125 firings)
        'hardt',
        # brid  (122 firings)
        ' Brid', ' brid',
        # idi  (119 firings)
        'idi',
        # pedd  (118 firings)
        ' pedd',
        # spac  (115 firings)
        ' spac', ' Spac',
        # tang  (112 firings)
        ' tang',
        # ando  (107 firings)
        'ando',
        # stad  (103 firings)
        'stad',
        # din  (98 firings)
        ' Din',
        # obsc  (86 firings)
        ' obsc',
        # sett  (84 firings)
        ' Sett', 'sett',
        # redist  (83 firings)
        ' redist',
        # rend  (79 firings)
        ' rend',
        # dialect  (79 firings)
        ' dialect',
        # hand  (78 firings)
        ' handic',
        # sand  (77 firings)
        ' Sands',
        # buck  (77 firings)
        'buck',
        # idad  (67 firings)
        'idad',
        # sidd  (67 firings)
        ' Sidd',
        # butt  (66 firings)
        ' Butt',
        # 380  (66 firings)
        '380',
        # sandbox  (66 firings)
        ' sandbox',
        # ippy  (62 firings)
        'ippy',
        # desmond  (61 firings)
        ' Desmond',
        # gri  (60 firings)
        ' Gri',
        # polit  (60 firings)
        ' polit',
        # tav  (59 firings)
        ' Tav',
        # trop  (56 firings)
        ' Trop',
        # sadd  (54 firings)
        ' Sadd',
        # gast  (54 firings)
        ' gast',
        # ast  (53 firings)
        ' Aster',
        # brune  (52 firings)
        ' Brune',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'sid-family', 1

def prog_L06F21975(input_tokens):
    """8 token families, 14 surface forms (train F1 of the uncapped optimum: 0.069).
    Fires at 83,399 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: phrases related to the action of launching initiatives or campaigns"""
    # --- end external annotation ---
    fire = {
        # a  (15,190 firings)
        ' a',
        # an  (3,359 firings)
        ' an',
        # its  (2,207 firings)
        ' its',
        # new  (1,841 firings)
        ' new',
        # launch  (1,223 firings)
        ' launch', ' launched', ' launching', ' launches', 'launch',
        # campaign  (541 firings)
        ' campaign', ' campaigns',
        # effort  (313 firings)
        ' effort', ' efforts',
        # major  (228 firings)
        ' major',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'a-family', 1

def prog_L06F21976(input_tokens):
    """13 token families, 14 surface forms (train F1 of the uncapped optimum: 0.172).
    Fires at 122,916 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: proper nouns, particularly names and surnames"""
    # --- end external annotation ---
    fire = {
        # man  (869 firings)
        'man', 'mans',
        # i  (843 firings)
        'i',
        # o  (713 firings)
        'o',
        # on  (608 firings)
        'on',
        # er  (603 firings)
        'er',
        # ie  (576 firings)
        'ie',
        # en  (547 firings)
        'en',
        # ley  (533 firings)
        'ley',
        # an  (531 firings)
        'an',
        # is  (476 firings)
        'is',
        # z  (396 firings)
        'z',
        # ner  (332 firings)
        'ner',
        # son  (315 firings)
        'son',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'man-family', 1

def prog_L06F21977(input_tokens):
    """7 token families, 12 surface forms (train F1 of the uncapped optimum: 0.144).
    Fires at 31,027 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: phrases that indicate struggling with various personal or mental health challenges"""
    # --- end external annotation ---
    fire = {
        # with  (13,291 firings)
        ' with',
        # fac  (931 firings)
        ' facing', ' faced',
        # battl  (434 firings)
        ' battling', ' battled',
        # experienc  (184 firings)
        ' experiencing',
        # overcome  (113 firings)
        ' overcome',
        # endur  (86 firings)
        ' endured', ' enduring',
        # confront  (82 firings)
        ' confront', ' confronting', ' confronts',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'with-family', 1

def prog_L06F21978(input_tokens):
    """34 token families, 40 surface forms (train F1 of the uncapped optimum: 0.561).
    Fires at 7,491 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to medications and their prescriptions"""
    # --- end external annotation ---
    fire = {
        # drug  (469 firings)
        ' drugs',
        # medicine  (400 firings)
        ' medicine',
        # pill  (388 firings)
        ' pills', ' pill',
        # pharmaceut  (334 firings)
        ' pharmaceutical', ' Pharmaceutical',
        # medica  (230 firings)
        ' medication',
        # treat  (205 firings)
        ' treatments',
        # medication  (166 firings)
        ' medications',
        # psychiatrist  (159 firings)
        ' psychiatrist', ' psychiatrists',
        # therapy  (136 firings)
        ' therapy',
        # medicin  (133 firings)
        ' medicines',
        # prescrib  (120 firings)
        ' prescribed',
        # vaccine  (119 firings)
        ' vaccine',
        # kill  (118 firings)
        'killers', 'killer',
        # antidepressant  (103 firings)
        ' antidepressants', ' antidepressant',
        # imen  (59 firings)
        'imen', 'imens',
        # ratom  (56 firings)
        'ratom',
        # counsel  (54 firings)
        ' counseling',
        # het  (53 firings)
        'heter',
        # regimen  (49 firings)
        ' regimen',
        # narcotic  (48 firings)
        ' narcotics',
        # morphine  (45 firings)
        ' morphine',
        # neurotran  (42 firings)
        ' neurotrans',
        # lydia  (40 firings)
        ' Lydia',
        # aspirin  (39 firings)
        ' aspirin',
        # bipolar  (39 firings)
        ' bipolar',
        # intervention  (38 firings)
        ' interventions',
        # psychiatry  (36 firings)
        ' psychiatry',
        # hyperten  (33 firings)
        ' hypertension',
        # idine  (28 firings)
        'idine',
        # prescribe  (28 firings)
        ' prescribe',
        # agra  (25 firings)
        'agra',
        # workaround  (24 firings)
        ' workaround',
        # ophen  (19 firings)
        'ophen',
        # dosage  (19 firings)
        ' dosage',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'drug-family', 1

def prog_L06F21979(input_tokens):
    """21 token families, 35 surface forms (train F1 of the uncapped optimum: 0.222).
    Fires at 43,972 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to career-high statistics in sports"""
    # --- end external annotation ---
    fire = {
        # high  (2,180 firings)
        ' high', ' highest', 'high', ' highs', 'highest', ' HIGH', ' Highest',
        # record  (1,162 firings)
        ' record', 'record', ' Record',
        # champion  (603 firings)
        ' champion', ' Champion', ' champions',
        # double  (546 firings)
        ' double', 'double',
        # larg  (499 firings)
        ' largest',
        # tot  (413 firings)
        ' total',
        # straight  (338 firings)
        ' straight', 'straight',
        # gold  (336 firings)
        ' gold',
        # winn  (251 firings)
        'winning', 'winner',
        # consecut  (238 firings)
        ' consecutive',
        # milestone  (219 firings)
        ' milestone',
        # long  (178 firings)
        ' longest',
        # multi  (174 firings)
        ' multi',
        # crim  (168 firings)
        ' crimes',
        # break  (166 firings)
        'breaking',
        # triple  (141 firings)
        ' triple', ' Triple',
        # med  (137 firings)
        ' medal',
        # whopp  (135 firings)
        ' whopping',
        # streak  (129 firings)
        ' streak',
        # best  (125 firings)
        'best',
        # fast  (112 firings)
        ' fastest',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'high-family', 1

def prog_L06F21980(input_tokens):
    """20 token families, 37 surface forms (train F1 of the uncapped optimum: 0.315).
    Fires at 52,689 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: terms related to embodiment, manifestation, and incarnation, often in political or philosophical contexts"""
    # --- end external annotation ---
    fire = {
        # ver  (632 firings)
        ' version', 'version',
        # example  (564 firings)
        ' example',
        # product  (411 firings)
        ' product', 'product', 'products',
        # victim  (383 firings)
        ' victim',
        # representat  (375 firings)
        ' representative', ' representatives',
        # adapta  (280 firings)
        ' adaptation',
        # shadow  (213 firings)
        ' shadow', ' shadows', 'shadow',
        # version  (205 firings)
        ' versions', 'versions',
        # reflec  (195 firings)
        ' reflection',
        # symbol  (194 firings)
        ' symbol', ' symbols',
        # exampl  (194 firings)
        ' examples', ' Examples', 'Examples',
        # expres  (189 firings)
        ' expression', 'expression',
        # exten  (186 firings)
        ' extension',
        # height  (164 firings)
        ' height',
        # itera  (156 firings)
        ' iteration',
        # blow  (155 firings)
        ' blow',
        # echo  (148 firings)
        ' echo', ' echoes', 'echo', ' echoing',
        # ess  (147 firings)
        ' essence', 'esses', ' Essence', 'essment',
        # defini  (144 firings)
        ' definition',
        # portrait  (133 firings)
        ' portrait',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'ver-family', 1

def prog_L06F21981(input_tokens):
    """19 token families, 34 surface forms (train F1 of the uncapped optimum: 0.740).
    Fires at 11,393 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to prisons and incarceration"""
    # --- end external annotation ---
    fire = {
        # prison  (3,788 firings)
        ' prison', ' prisons', ' Prison', ' prisoners', ' prisoner', 'prison',
        # jail  (1,432 firings)
        ' jail', ' Jail', ' jails',
        # deten  (601 firings)
        ' detention', ' Detention',
        # imprison  (308 firings)
        ' imprisoned', ' imprisonment', ' imprison',
        # correction  (287 firings)
        ' Corrections', ' Correctional', ' correctional', ' corrections',
        # guantanamo  (189 firings)
        ' Guantanamo',
        # pr  (141 firings)
        'Pr',
        # incarcera  (126 firings)
        ' incarceration',
        # pen  (124 firings)
        ' penal', ' Penal',
        # confine  (106 firings)
        ' confinement',
        # arkham  (105 firings)
        ' Arkham',
        # ison  (105 firings)
        'ISON', 'isons',
        # incarcerat  (90 firings)
        ' incarcerated',
        # auschwitz  (66 firings)
        ' Auschwitz',
        # ihar  (45 firings)
        'ihar',
        # guant  (45 firings)
        ' Guant',
        # png  (33 firings)
        ' PNG',
        # hogwart  (29 firings)
        ' Hogwarts',
        # labyrinth  (29 firings)
        ' Labyrinth',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'prison-family', 1

def prog_L06F21982(input_tokens):
    """31 token families, 39 surface forms (train F1 of the uncapped optimum: 0.740).
    Fires at 11,387 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: instances of the word "ag" in various contexts"""
    # --- end external annotation ---
    fire = {
        # ig  (3,888 firings)
        'ig', 'IG', ' ig',
        # rig  (300 firings)
        'rig', ' Rig',
        # lig  (242 firings)
        ' lig', 'lig',
        # iger  (233 firings)
        'iger',
        # oug  (193 firings)
        'oug',
        # miguel  (190 firings)
        ' Miguel',
        # igs  (186 firings)
        'igs',
        # gig  (153 firings)
        ' Gig',
        # zig  (147 firings)
        'zig', ' Zig',
        # wig  (132 firings)
        ' wig', 'wig',
        # iga  (131 firings)
        'iga',
        # igo  (117 firings)
        'igo',
        # pig  (99 firings)
        ' Pig',
        # mig  (90 firings)
        ' Mig', ' mig',
        # lich  (84 firings)
        'lich',
        # igel  (80 firings)
        'igel',
        # dou  (65 firings)
        'Dou',
        # dig  (65 firings)
        'dig',
        # berk  (64 firings)
        ' Berk',
        # igi  (62 firings)
        'igi',
        # __  (56 firings)
        '__',
        # igg  (51 firings)
        'igger',
        # nig  (45 firings)
        ' Nig', ' nig',
        # igne  (42 firings)
        'igne',
        # eyel  (41 firings)
        ' eyel',
        # aber  (40 firings)
        'aber',
        # igil  (39 firings)
        'igil',
        # fairy  (39 firings)
        ' Fairy',
        # ________  (34 firings)
        '________',
        # ー  (34 firings)
        'ー',
        # ー�  (31 firings)
        'ー�',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'ig-family', 1

def prog_L06F21983(input_tokens):
    """34 token families, 35 surface forms (train F1 of the uncapped optimum: 0.451).
    Fires at 2,931 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: special characters or non-standard symbols in the text"""
    # --- end external annotation ---
    fire = {
        # semif  (99 firings)
        ' semif',
        # iny  (82 firings)
        'iny',
        # lowe  (80 firings)
        ' Lowe',
        # м  (78 firings)
        'м',
        # dup  (69 firings)
        ' Dup',
        # finalist  (58 firings)
        ' finalists',
        # ————  (52 firings)
        '————',
        # kle  (43 firings)
        ' Kle',
        # supplement  (41 firings)
        ' Supplemental',
        # cut  (37 firings)
        'Cut',
        # nette  (36 firings)
        'nette',
        # τ  (33 firings)
        'τ',
        # sug  (33 firings)
        ' Sug',
        # incom  (32 firings)
        ' incom',
        # sponge  (27 firings)
        ' Sponge',
        # shrunk  (25 firings)
        ' shrunk',
        # slight  (22 firings)
        ' Slightly',
        # unc  (22 firings)
        ' UNC',
        # ————————  (21 firings)
        '————————',
        # て  (20 firings)
        'て',
        # uper  (20 firings)
        'uper',
        # ∼  (18 firings)
        ' ∼',
        # ト  (14 firings)
        'ト',
        # ↑  (14 firings)
        ' ↑', '↑',
        # roxy  (13 firings)
        'roxy',
        # >=  (13 firings)
        ' >=',
        # し  (13 firings)
        'し',
        # ille  (12 firings)
        'ILLE',
        # プ  (11 firings)
        'プ',
        # centimet  (11 firings)
        ' centimeters',
        # bonu  (10 firings)
        'Bonus',
        # מ  (9 firings)
        'מ',
        # ------------  (9 firings)
        '------------',
        # ++  (8 firings)
        ' ++',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'semif-family', 1

def prog_L06F21984(input_tokens):
    """1 token families, 1 surface forms (train F1 of the uncapped optimum: 0.549).
    Fires at 28,116 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: instances of the word "one" with varying contexts indicating unity or singularity"""
    # --- end external annotation ---
    fire = {
        # one  (24,490 firings)
        ' one',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'one-family', 1

def prog_L06F21985(input_tokens):
    """10 token families, 12 surface forms (train F1 of the uncapped optimum: 0.781).
    Fires at 8,287 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: the word "completely" and its variants in various contexts"""
    # --- end external annotation ---
    fire = {
        # complete  (2,525 firings)
        ' completely', 'completely',
        # entire  (1,051 firings)
        ' entirely',
        # total  (921 firings)
        ' totally', ' Totally',
        # thorough  (265 firings)
        ' thoroughly',
        # fundamental  (223 firings)
        ' fundamentally',
        # utter  (208 firings)
        ' utterly',
        # drastical  (170 firings)
        ' drastically',
        # radical  (149 firings)
        ' radically',
        # otal  (87 firings)
        'otally',
        # hand  (28 firings)
        'handedly',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'complete-family', 1

def prog_L06F21986(input_tokens):
    """34 token families, 37 surface forms (train F1 of the uncapped optimum: 0.553).
    Fires at 6,723 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to touchdowns in sports contexts"""
    # --- end external annotation ---
    fire = {
        # touchdown  (615 firings)
        ' touchdown', ' touchdowns',
        # championship  (587 firings)
        ' championship', ' championships',
        # delici  (361 firings)
        ' delicious',
        # test  (247 firings)
        ' Test',
        # tasty  (121 firings)
        ' tasty',
        # hom  (114 firings)
        ' homer', ' homers',
        # td  (96 firings)
        ' TD',
        # interception  (80 firings)
        ' interceptions',
        # intercep  (75 firings)
        ' interception',
        # heisman  (73 firings)
        ' Heisman',
        # verb  (70 firings)
        ' verb',
        # thc  (70 firings)
        ' THC',
        # reception  (69 firings)
        ' receptions',
        # catchy  (62 firings)
        ' catchy',
        # rebound  (59 firings)
        ' rebounds',
        # iership  (58 firings)
        'iership',
        # tds  (54 firings)
        ' TDs',
        # noun  (52 firings)
        ' noun',
        # ethanol  (50 firings)
        ' ethanol',
        # strikeout  (47 firings)
        ' strikeouts',
        # orgasm  (46 firings)
        ' orgasm',
        # mbp  (45 firings)
        'Mbps',
        # flavor  (41 firings)
        ' flavorful',
        # fumble  (40 firings)
        ' fumble',
        # dunk  (38 firings)
        ' dunk',
        # melody  (36 firings)
        ' melody',
        # sunrise  (34 firings)
        ' sunrise',
        # igni  (33 firings)
        ' ignition',
        # timeout  (30 firings)
        ' timeout',
        # point  (25 firings)
        'pointers',
        # melod  (25 firings)
        ' melodies',
        # climax  (23 firings)
        ' climax',
        # righte  (22 firings)
        ' righteous',
        # abv  (20 firings)
        ' ABV',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'touchdown-family', 1

def prog_L06F21987(input_tokens):
    """16 token families, 16 surface forms (train F1 of the uncapped optimum: 0.191).
    Fires at 24,421 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: occurrences of specific names, particularly those of political figures"""
    # --- end external annotation ---
    fire = {
        # donald  (1,177 firings)
        ' Donald',
        # john  (971 firings)
        ' John',
        # |  (522 firings)
        ' |',
        # (@  (434 firings)
        ' (@',
        # invalid  (346 firings)
        ' invalid',
        # what  (220 firings)
        ' Whats',
        # house  (205 firings)
        'House',
        # speak  (196 firings)
        ' speaks',
        # urg  (181 firings)
        ' urges',
        # diane  (162 firings)
        ' Diane',
        # rodham  (156 firings)
        ' Rodham',
        # sand  (84 firings)
        'Sanders',
        # bernard  (79 firings)
        ' Bernard',
        # attend  (69 firings)
        ' attends',
        # bernie  (67 firings)
        'Bernie',
        # ·  (63 firings)
        ' ·',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'donald-family', 1

def prog_L06F21988(input_tokens):
    """47 token families, 56 surface forms (train F1 of the uncapped optimum: 0.590).
    Fires at 20,675 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to destruction or damage"""
    # --- end external annotation ---
    fire = {
        # wreck  (382 firings)
        ' wreck', 'wreck', ' wrecked',
        # embark  (349 firings)
        ' embark', ' embarked',
        # park  (345 firings)
        ' parked',
        # unleash  (342 firings)
        ' unleashed', ' unleash',
        # strand  (215 firings)
        ' stranded',
        # ruin  (213 firings)
        ' ruins', ' ruin',
        # shar  (212 firings)
        ' Shares',
        # inflict  (210 firings)
        ' inflicted', ' inflict', ' inflicting',
        # footprint  (209 firings)
        ' footprint', ' footprints',
        # spree  (191 firings)
        ' spree',
        # beast  (189 firings)
        ' beast',
        # rampage  (185 firings)
        ' rampage',
        # havoc  (184 firings)
        ' havoc',
        # wre  (170 firings)
        ' wre',
        # churn  (161 firings)
        ' churn',
        # slew  (161 firings)
        ' slew',
        # reck  (161 firings)
        'reck', ' Reck',
        # devasta  (139 firings)
        ' devastation',
        # batter  (138 firings)
        ' battered',
        # wreckage  (136 firings)
        ' wreckage',
        # spew  (131 firings)
        ' spew',
        # zack  (126 firings)
        ' Zack',
        # cks  (118 firings)
        'cks',
        # devastat  (116 firings)
        ' devastated',
        # onslaught  (112 firings)
        ' onslaught',
        # tuck  (111 firings)
        ' Tucker',
        # wip  (111 firings)
        ' wiped',
        # stre  (106 firings)
        ' stre',
        # mayhem  (104 firings)
        ' mayhem',
        # rav  (103 firings)
        ' rav',
        # crat  (102 firings)
        ' crater',
        # litter  (102 firings)
        ' littered',
        # monstr  (101 firings)
        ' monstrous',
        # rack  (96 firings)
        ' racked',
        # crippl  (95 firings)
        ' crippled',
        # carnage  (91 firings)
        ' carnage',
        # stomp  (90 firings)
        ' stomp',
        # swath  (89 firings)
        ' swath',
        # ravag  (84 firings)
        ' ravaged',
        # bedford  (79 firings)
        ' Bedford',
        # scourge  (76 firings)
        ' scourge',
        # perpetrat  (76 firings)
        ' perpetrated',
        # riddl  (75 firings)
        ' riddled',
        # ashore  (74 firings)
        ' ashore',
        # estead  (73 firings)
        'estead',
        # dere  (71 firings)
        ' dere',
        # poop  (70 firings)
        ' poop',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'wreck-family', 1

def prog_L06F21989(input_tokens):
    """10 token families, 15 surface forms (train F1 of the uncapped optimum: 0.057).
    Fires at 44,581 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: the end of sentences or paragraphs"""
    # --- end external annotation ---
    fire = {
        # new  (886 firings)
        ' new', ' NEW',
        # man  (497 firings)
        ' man', ' MAN',
        # group  (327 firings)
        ' group', ' GROUP', ' grouping',
        # form  (323 firings)
        ' former',
        # woman  (282 firings)
        ' woman',
        # study  (230 firings)
        ' study', ' Study',
        # friend  (197 firings)
        ' friend',
        # film  (170 firings)
        ' film',
        # couple  (167 firings)
        ' couple',
        # guest  (146 firings)
        ' guest',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'new-family', 1

def prog_L06F21990(input_tokens):
    """26 token families, 52 surface forms (train F1 of the uncapped optimum: 0.239).
    Fires at 40,088 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to competitive rankings or awards, especially in the context of individuals or entities being recognized"""
    # --- end external annotation ---
    fire = {
        # up  (872 firings)
        'up',
        # winn  (648 firings)
        ' winner', ' winners', ' Winner', 'winner', ' Winners', 'Winner',
        # champion  (557 firings)
        ' champion', ' Champion', ' champions',
        # elect  (514 firings)
        'elect',
        # runn  (426 firings)
        'runner', ' runner', 'runners', ' runners', 'Runner',
        # entry  (350 firings)
        ' entry', ' Entry',
        # year  (258 firings)
        ' Year',
        # overall  (256 firings)
        ' overall',
        # selec  (245 firings)
        ' selection', ' Selection', 'selection',
        # mate  (238 firings)
        ' mate', 'mate',
        # star  (228 firings)
        'Star', 'Stars', 'stars',
        # med  (219 firings)
        ' medal',
        # play  (209 firings)
        ' Player',
        # lin  (179 firings)
        'lining', 'liner', 'liners',
        # seed  (173 firings)
        ' seed', 'seed', ' seeded',
        # row  (168 firings)
        ' row', 'rower',
        # ring  (157 firings)
        'ring',
        # prize  (156 firings)
        ' prize',
        # choice  (138 firings)
        ' Choice', 'choice',
        # card  (135 firings)
        'card', 'cards',
        # uts  (132 firings)
        'uts',
        # iser  (120 firings)
        'iser',
        # contend  (111 firings)
        ' contenders', ' contender',
        # hard  (108 firings)
        'hard',
        # entr  (102 firings)
        ' entries',
        # hold  (101 firings)
        ' holder', 'holder',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'up-family', 1

def prog_L06F21991(input_tokens):
    """22 token families, 30 surface forms (train F1 of the uncapped optimum: 0.695).
    Fires at 7,353 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to "feet" in various contexts"""
    # --- end external annotation ---
    fire = {
        # feet  (1,693 firings)
        ' feet', 'feet', ' Feet',
        # foot  (1,487 firings)
        ' foot', 'foot', ' footing', 'footed', 'Foot',
        # boot  (259 firings)
        ' boots', ' Boots',
        # ankle  (253 firings)
        ' ankle',
        # footprint  (212 firings)
        ' footprint', ' footprints',
        # mil  (186 firings)
        ' Miles',
        # footstep  (161 firings)
        ' footsteps',
        # stair  (122 firings)
        ' stairs',
        # sock  (112 firings)
        ' socks',
        # floor  (98 firings)
        ' floors',
        # toe  (88 firings)
        ' toes',
        # doorstep  (83 firings)
        ' doorstep',
        # foothold  (61 firings)
        ' foothold',
        # stride  (61 firings)
        ' stride',
        # fingertip  (53 firings)
        ' fingertips',
        # fts  (41 firings)
        'fts',
        # ankl  (39 firings)
        ' ankles',
        # ph  (36 firings)
        ' pH',
        # paw  (36 firings)
        ' paws',
        # ranean  (33 firings)
        'ranean',
        # misty  (28 firings)
        ' Misty',
        # ground  (19 firings)
        ' grounding',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'feet-family', 1

def prog_L06F21992(input_tokens):
    """50 token families, 52 surface forms (train F1 of the uncapped optimum: 0.668).
    Fires at 14,683 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to international locations and legal contexts"""
    # --- end external annotation ---
    fire = {
        # switzerland  (445 firings)
        ' Switzerland',
        # geneva  (328 firings)
        ' Geneva',
        # damascu  (316 firings)
        ' Damascus',
        # vienna  (227 firings)
        ' Vienna',
        # haven  (226 firings)
        ' Haven', 'haven',
        # hague  (173 firings)
        ' Hague',
        # durham  (150 firings)
        ' Durham',
        # lavrov  (127 firings)
        ' Lavrov',
        # sergei  (126 firings)
        ' Sergei',
        # gene  (125 firings)
        'Gene',
        # oslo  (122 firings)
        ' Oslo',
        # godzilla  (121 firings)
        ' Godzilla',
        # wembley  (120 firings)
        ' Wembley',
        # calai  (119 firings)
        ' Calais',
        # flor  (115 firings)
        ' Florence',
        # windsor  (114 firings)
        ' Windsor',
        # il  (113 firings)
        ' IL',
        # millennium  (112 firings)
        ' Millennium',
        # hell  (111 firings)
        ' Heller',
        # gas  (110 firings)
        ' gases',
        # riyadh  (104 firings)
        ' Riyadh',
        # eca  (103 firings)
        'eca', 'ECA',
        # gen  (102 firings)
        'GEN',
        # specific  (101 firings)
        ' specifics',
        # cann  (98 firings)
        ' Cannes',
        # zurich  (98 firings)
        ' Zurich',
        # infrar  (97 firings)
        ' infrared',
        # copenhagen  (96 firings)
        ' Copenhagen',
        # idlib  (95 firings)
        ' Idlib',
        # laurie  (94 firings)
        ' Laurie',
        # dayton  (94 firings)
        ' Dayton',
        # goodell  (92 firings)
        ' Goodell',
        # essa  (90 firings)
        'essa',
        # hartford  (89 firings)
        ' Hartford',
        # norri  (87 firings)
        ' Norris',
        # kyoto  (85 firings)
        ' Kyoto',
        # lisbon  (83 firings)
        ' Lisbon',
        # stra  (81 firings)
        ' Stras',
        # hyde  (81 firings)
        ' Hyde',
        # 1949  (81 firings)
        ' 1949',
        # louise  (80 firings)
        ' Louise',
        # lancet  (79 firings)
        ' Lancet',
        # eva  (76 firings)
        'EVA',
        # helsinki  (76 firings)
        ' Helsinki',
        # insk  (71 firings)
        'insk',
        # cornwall  (68 firings)
        ' Cornwall',
        # hiroshima  (65 firings)
        ' Hiroshima',
        # naomi  (65 firings)
        ' Naomi',
        # indiffer  (61 firings)
        ' indifference',
        # dresden  (61 firings)
        ' Dresden',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'switzerland-family', 1

def prog_L06F21993(input_tokens):
    """5 token families, 7 surface forms (train F1 of the uncapped optimum: 0.111).
    Fires at 46,672 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: pronouns, particularly "they" and "it," indicating a focus on subjects and their relationships in statements"""
    # --- end external annotation ---
    fire = {
        # it  (8,534 firings)
        ' it',
        # they  (5,345 firings)
        ' they', 'they',
        # he  (4,598 firings)
        ' he',
        # she  (1,372 firings)
        ' she',
        # fear  (167 firings)
        ' fear', ' feared',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'it-family', 1

def prog_L06F21994(input_tokens):
    """41 token families, 59 surface forms (train F1 of the uncapped optimum: 0.588).
    Fires at 19,382 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: phrases related to praise or acclaim"""
    # --- end external annotation ---
    fire = {
        # hail  (515 firings)
        ' hailed', ' hail', ' Hail',
        # blast  (449 firings)
        ' blasted', ' blasting',
        # await  (444 firings)
        'awaited', ' awaited',
        # welcom  (427 firings)
        ' welcomed',
        # tout  (408 firings)
        ' touted', ' touting',
        # pra  (388 firings)
        ' praised',
        # acclaim  (365 firings)
        ' acclaimed', ' acclaim',
        # proclaim  (364 firings)
        ' proclaimed', ' proclaiming', ' proclaim', 'proclaimed',
        # celebrat  (344 firings)
        ' celebrated',
        # ail  (305 firings)
        'ailing', 'ailed',
        # greet  (289 firings)
        ' greeted',
        # bill  (283 firings)
        ' billed', ' billing',
        # herald  (223 firings)
        ' herald',
        # glori  (203 firings)
        ' glorious',
        # laud  (200 firings)
        ' lauded', ' laud',
        # slamm  (196 firings)
        ' slammed',
        # crown  (170 firings)
        ' crowned',
        # overview  (160 firings)
        'Overview',
        # roar  (153 firings)
        ' roaring', ' roar', ' roared',
        # shap  (149 firings)
        ' shaping',
        # call  (140 firings)
        'Calling', ' Calling',
        # mighty  (137 firings)
        ' Mighty', ' mighty',
        # oft  (133 firings)
        ' oft',
        # denounc  (126 firings)
        ' denounced', ' denouncing',
        # reel  (117 firings)
        ' reeling',
        # breakout  (117 firings)
        ' breakout',
        # champion  (116 firings)
        ' championed',
        # accol  (113 firings)
        ' accol',
        # reet  (106 firings)
        'reetings',
        # celebr  (104 firings)
        ' Celebr', ' celebr',
        # cheer  (95 firings)
        ' cheered',
        # ounc  (90 firings)
        'ouncing',
        # triumphant  (84 firings)
        ' triumphant',
        # lament  (81 firings)
        ' lamented',
        # renaiss  (80 firings)
        ' renaissance',
        # prais  (78 firings)
        ' praises',
        # cele  (68 firings)
        ' cele',
        # payday  (65 firings)
        ' payday',
        # cohn  (56 firings)
        ' Cohn',
        # synopsi  (56 firings)
        'Synopsis',
        # rejoice  (51 firings)
        ' rejoice',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'hail-family', 1

def prog_L06F21995(input_tokens):
    """36 token families, 40 surface forms (train F1 of the uncapped optimum: 0.756).
    Fires at 5,941 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to lists or items in a structured format"""
    # --- end external annotation ---
    fire = {
        # li  (872 firings)
        'li', 'LI', ' li',
        # •  (359 firings)
        ' •',
        # lli  (313 firings)
        'lli',
        # oni  (234 firings)
        'oni',
        # eli  (209 firings)
        ' Eli', 'eli',
        # lem  (202 firings)
        ' Lem',
        # colt  (195 firings)
        ' Colts',
        # fath  (172 firings)
        ' Father',
        # oli  (164 firings)
        'oli',
        # liu  (150 firings)
        ' Liu',
        # whol  (132 firings)
        ' wholly',
        # gan  (130 firings)
        ' Gan',
        # lionel  (126 firings)
        ' Lionel',
        # lie  (124 firings)
        'lie',
        # liga  (108 firings)
        ' Liga', 'liga',
        # oshi  (104 firings)
        'oshi',
        # stre  (103 firings)
        ' stre',
        # tolkien  (103 firings)
        ' Tolkien',
        # ti  (81 firings)
        'ti',
        # ll  (78 firings)
        ' Ll',
        # tti  (73 firings)
        'tti',
        # del  (67 firings)
        ' DeL',
        # sweeney  (60 firings)
        ' Sweeney',
        # zhang  (60 firings)
        ' Zhang',
        # levi  (58 firings)
        ' Levi',
        # 330  (49 firings)
        ' 330',
        # ogh  (46 firings)
        'ogh',
        # manit  (46 firings)
        ' Manit',
        # lei  (39 firings)
        ' Lei',
        # cabbage  (35 firings)
        ' cabbage',
        # lv  (35 firings)
        'lv',
        # liv  (32 firings)
        ' Liver',
        # vertical  (31 firings)
        ' vertically',
        # liang  (25 firings)
        ' Liang',
        # eliot  (23 firings)
        ' Eliot',
        # fraz  (18 firings)
        ' Fraz',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'li-family', 1

def prog_L06F21996(input_tokens):
    """18 token families, 42 surface forms (train F1 of the uncapped optimum: 0.158).
    Fires at 191,560 of 36,786,566 positions.
    Fires at 0.52% of positions, and
    token rules do not serve features this dense: median test F1 0.086
    across the 37,173 features above 0.39% of positions, against 0.763 for
    the 76,283 below 0.016%. Read this fire set as the best available
    approximation, not as what the feature does."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: reports that contain statistical data or findings on social issues"""
    # --- end external annotation ---
    fire = {
        # that  (10,959 firings)
        ' that',
        # report  (3,169 firings)
        ' report', ' Report',
        # releas  (2,926 firings)
        ' released', 'released', 'Released',
        # found  (2,032 firings)
        ' found',
        # show  (1,804 firings)
        ' shows', ' showed', ' showing', 'shows',
        # study  (1,491 firings)
        ' study', ' Study', 'study',
        # announc  (1,353 firings)
        ' announced',
        # say  (1,314 firings)
        ' says',
        # publish  (1,249 firings)
        ' published',
        # wednesday  (1,124 firings)
        ' Wednesday',
        # warn  (956 firings)
        ' warned', ' warning', ' warns', ' warn',
        # research  (946 firings)
        ' research', ' researchers', 'Researchers', ' Researchers', 'Research',
        # suggest  (855 firings)
        ' suggests', ' suggested', ' suggesting',
        # reveal  (832 firings)
        ' revealed', ' reveals', ' revealing',
        # issu  (790 firings)
        ' issued',
        # find  (615 firings)
        ' finds', ' findings', 'finding',
        # conclud  (541 firings)
        ' concluded', ' concludes', ' concluding',
        # annu  (519 firings)
        ' annual', ' Annual',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'that-family', 1

def prog_L06F21997(input_tokens):
    """2 token families, 2 surface forms (train F1 of the uncapped optimum: 0.277).
    Fires at 2,576 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: mentions of the website "twitter.com" """
    # --- end external annotation ---
    fire = {
        # com  (1,703 firings)
        'com',
        # twitt  (238 firings)
        'twitter',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'com-family', 1

def prog_L06F21998(input_tokens):
    """48 token families, 48 surface forms (train F1 of the uncapped optimum: 0.693).
    Fires at 7,387 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to the city of Mosul and its associated events or situations"""
    # --- end external annotation ---
    fire = {
        # mosul  (381 firings)
        ' Mosul',
        # glasgow  (341 firings)
        ' Glasgow',
        # baghdad  (225 firings)
        ' Baghdad',
        # airstrik  (216 firings)
        ' airstrikes',
        # map  (216 firings)
        ' Maps',
        # pluto  (165 firings)
        ' Pluto',
        # ramadan  (142 firings)
        ' Ramadan',
        # nim  (124 firings)
        ' Nim',
        # katrina  (119 firings)
        ' Katrina',
        # pesh  (116 firings)
        ' Pesh',
        # bil  (114 firings)
        'bil',
        # rubble  (114 firings)
        ' rubble',
        # karachi  (111 firings)
        ' Karachi',
        # yaz  (108 firings)
        ' Yaz',
        # airstrike  (106 firings)
        ' airstrike',
        # abram  (105 firings)
        ' Abrams',
        # trafford  (100 firings)
        ' Trafford',
        # airo  (96 firings)
        'airo',
        # ryzen  (91 firings)
        ' Ryzen',
        # unesco  (90 firings)
        ' UNESCO',
        # petraeu  (88 firings)
        ' Petraeus',
        # rav  (86 firings)
        ' rav',
        # myra  (85 firings)
        'myra',
        # aghd  (76 firings)
        'aghd',
        # spear  (75 firings)
        ' Spears',
        # daesh  (74 firings)
        ' Daesh',
        # polio  (65 firings)
        ' polio',
        # retake  (60 firings)
        ' retake',
        # ujah  (59 firings)
        'ujah',
        # manziel  (59 firings)
        ' Manziel',
        # kun  (59 firings)
        ' Kun',
        # agar  (58 firings)
        'agar',
        # mos  (57 firings)
        'Mos',
        # ima  (54 firings)
        'imation',
        # ulia  (53 firings)
        'ulia',
        # loch  (46 firings)
        ' Loch',
        # iyah  (43 firings)
        'iyah',
        # mar  (42 firings)
        ' mars',
        # geo  (40 firings)
        ' Geo',
        # kund  (32 firings)
        ' Kund',
        # hitman  (27 firings)
        ' Hitman',
        # unicode  (26 firings)
        ' Unicode',
        # shinji  (24 firings)
        ' Shinji',
        # ukong  (24 firings)
        'ukong',
        # 6000  (23 firings)
        ' 6000',
        # baghd  (22 firings)
        ' Baghd',
        # upit  (22 firings)
        'upiter',
        # mus  (21 firings)
        ' MUS',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'mosul-family', 1

def prog_L06F21999(input_tokens):
    """30 token families, 38 surface forms (train F1 of the uncapped optimum: 0.675).
    Fires at 7,674 of 36,786,566 positions."""
    # --- begin external annotation (ignored at runtime) ---
    """prev SAE description: references to various types of cells in biological contexts, particularly immune and stem cells"""
    # --- end external annotation ---
    fire = {
        # cell  (2,686 firings)
        ' cells', ' cell', ' Cell', ' Cells', 'cells',
        # organism  (248 firings)
        ' organisms', ' organism',
        # neuron  (246 firings)
        ' neurons', ' neuronal', ' neuron',
        # embryo  (142 firings)
        ' embryos', ' embryo',
        # galax  (114 firings)
        ' galaxies',
        # organ  (96 firings)
        ' organs',
        # cellular  (75 firings)
        ' cellular',
        # lymph  (71 firings)
        ' lymph',
        # coc  (71 firings)
        ' coc',
        # leukemia  (69 firings)
        ' leukemia',
        # nucle  (61 firings)
        ' nucle',
        # regen  (51 firings)
        ' regener',
        # marrow  (48 firings)
        ' marrow',
        # llular  (47 firings)
        'llular',
        # rna  (47 firings)
        ' RNA',
        # obl  (45 firings)
        'obl',
        # embryon  (38 firings)
        ' embryonic',
        # bud  (36 firings)
        ' buds',
        # acteria  (34 firings)
        'acteria',
        # ube  (30 firings)
        'ubes',
        # ocyt  (29 firings)
        'ocytes',
        # ucle  (29 firings)
        'ucle',
        # differentia  (25 firings)
        ' differentiation',
        # deriv  (25 firings)
        'derived',
        # clot  (25 firings)
        ' clot',
        # plur  (24 firings)
        ' plur',
        # regenerate  (24 firings)
        ' regenerate',
        # chromosom  (23 firings)
        ' chromosomes',
        # otent  (23 firings)
        'otent',
        # hel  (22 firings)
        'helial',
    }
    token = input_tokens[-1]
    if token not in fire:
        return "no match", 0
    return 'cell-family', 1