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Ancient Greek (to 1453)
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83dae89 667319c 83dae89 531a22f 83dae89 531a22f 83dae89 531a22f 83dae89 6fc8784 1e6d8b5 6fc8784 13ef6e2 265998e 6fc8784 265998e 6fc8784 265998e 6fc8784 265998e 6fc8784 265998e 6fc8784 13ef6e2 6fc8784 265998e 6fc8784 13ef6e2 265998e 13ef6e2 6fc8784 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 | """Uniform preprocessing and UD-v2 normalization for automatic syntax."""
from __future__ import annotations
import unicodedata
UNIVERSAL_DEPRELS = frozenset({
"acl", "advcl", "advmod", "amod", "appos", "aux", "case", "cc",
"ccomp", "clf", "compound", "conj", "cop", "csubj", "dep", "det",
"discourse", "dislocated", "expl", "fixed", "flat", "goeswith", "iobj",
"list", "mark", "nmod", "nsubj", "nummod", "obj", "obl", "orphan",
"parataxis", "punct", "reparandum", "root", "vocative", "xcomp",
})
# Hypotactic also uses these apostrophe/koronis characters as token-attached
# marks. Unicode does not classify all of them as punctuation.
PUNCTUATION_LIKE = frozenset({"ʼ", "᾽", "᾿", "῾"})
def is_editorial_punctuation(character: str) -> bool:
"""Punctuation, symbols and digits are apparatus, never the author's Greek.
Symbols (category S) cover the angle brackets of editorial supplements
(<ἄλαστ>), the tilde and acute some files use for a circumflex or accent
(δι~ος, ει´κω) and the spacing breathings (῎, ῞) written before a capital.
Digits (category N) are Morpheus sense indices on lemmas (λέγω3), which
only some projects write, and stray line numbers glued to a form
(ἔλλαχες1). Each of them survives in the files of a few authors only.
"""
return unicodedata.category(character)[0] in "PSN" or character in PUNCTUATION_LIKE
def punctuationless_tokens(token: str) -> list[str]:
"""Remove punctuation, treating it as a boundary rather than joining words."""
cleaned = "".join(
" " if is_editorial_punctuation(character) else character
for character in token
)
return [
piece for piece in cleaned.split()
if any(character.isalpha() for character in piece)
]
def punctuationless_lemma(lemma: str) -> str:
"""Remove any punctuation a tagger retained or generated inside a lemma."""
return "".join(punctuationless_tokens(lemma)) or "_"
def syntax_text_normalize(value: str) -> str:
"""Normalize letters for punctuationless parser span and coverage checks.
The same reduction as ``tracks.normalize``: lowercased Greek letters with
final sigma folded and no diacritics, without the archaic numeral letters
(stigma, digamma, koppa, sampi), which the parser's tokeniser drops. Every
span, crop and coverage check must measure text the same way.
"""
return "".join(
character
for character in unicodedata.normalize("NFD", value.lower().replace("ς", "σ"))
if unicodedata.category(character) != "Mn"
and "\u0370" <= character <= "\u03ff" and character.isalpha()
and not ("\u03da" <= character <= "\u03e1")
)
def canonical_stoicheia_deprel(relation: str | None, upos: str, head: int) -> str:
"""Return a UD-v2 relation, repairing Stoicheia's residual AGDT labels."""
if head == 0:
return "root"
raw = (relation or "dep").strip()
base, separator, subtype = raw.partition(":")
lower_base = base.lower()
if lower_base in UNIVERSAL_DEPRELS:
return lower_base + (f":{subtype.lower()}" if separator and subtype else "")
legacy = {
"auxp": "case",
"auxc": "cc" if upos == "CCONJ" else "mark",
"auxv": "aux",
"auxy": "discourse",
"auxz": "advmod",
}
return legacy.get(lower_base, "dep")
def is_universal_deprel(relation: str) -> bool:
return relation.split(":", 1)[0] in UNIVERSAL_DEPRELS
def normalize_cc_heads(ids: list[int], heads: list[int], deprels: list[str]) -> list[int]:
"""Attach every coordinator to the conjunct that follows it.
The projects disagree about where ``cc`` hangs: PROIEL puts it on the
conjunct after the conjunction, as the UD guidelines say, UD Perseus on
the first conjunct, and a parser trained on both does either. Since the
projects' author inventories do not overlap, the difference named the
author. Every layer and every project is reduced to the guideline here.
A coordinator with no conjunct after it (καί opening a sentence, a
postposed τε) stays on the last member, which is the coordination head
itself when there is no ``conj`` at all.
"""
position = {token_id: index for index, token_id in enumerate(ids)}
base = [deprel.split(":", 1)[0] if deprel else "" for deprel in deprels]
conjuncts: dict[int, list[int]] = {}
for token_id, head, relation in zip(ids, heads, base):
if relation == "conj" and head in position:
conjuncts.setdefault(head, []).append(token_id)
output = list(heads)
for index, (token_id, head, relation) in enumerate(zip(ids, heads, base)):
if relation != "cc" or head not in position:
continue
governor = head
if base[position[head]] == "conj" and heads[position[head]] in position:
governor = heads[position[head]]
members = [governor, *sorted(conjuncts.get(governor, []))]
following = [member for member in members if member > token_id]
output[index] = following[0] if following else members[-1]
return output
# ---------------------------------------------------------------------------
# Scheme-neutral model-facing normalization.
#
# Sphragis merges seven annotation projects whose author inventories do not
# overlap, so any convention that distinguishes those projects also identifies
# the author. The mappings below reduce every source to one shared inventory,
# so that a category boundary the projects disagree about cannot be used as an
# authorship feature. See metadata/leakage_report.json for the measured effect.
# ---------------------------------------------------------------------------
# AGDT nine-position part of speech (XPOS position 1) after normalization.
# ``l``/``p`` (article, pronoun) and ``d``/``g``/``c``/``b`` (adverb, particle,
# conjunction) are merged because the projects disagree about exactly these
# boundaries for the highest-frequency Greek function words: δέ is a particle
# in AGDT, an adverb in Gorman and a coordinator in UD Perseus; καί is a
# subordinator in the AGDT lineage and a coordinator in UD.
CORE_XPOS_POS = {
"n": "n", "v": "v", "t": "v", "a": "a",
"p": "p", "l": "p",
"d": "d", "g": "d", "c": "d", "b": "d",
"r": "r", "m": "m", "i": "i",
"u": "u",
"x": "x", "e": "x", "z": "x", "-": "x",
}
CORE_XPOS_TO_UPOS = {
"n": "NOUN", "v": "VERB", "a": "ADJ", "p": "PRON", "d": "ADV",
"r": "ADP", "m": "NUM", "i": "INTJ", "u": "PUNCT", "x": "X",
}
# Morphological features published for every token. ``PronType``,
# ``Definite``, ``Polarity``, ``Poss`` and ``Reflex`` are excluded because they
# occur in one project only. ``Aspect`` and ``VerbForm`` are included but never
# taken from a source project, for the same reason: the build derives them
# from the normalized XPOS, uniformly, in canonical_feats below.
CORE_FEATS = (
"Aspect", "Case", "Degree", "Gender", "Mood", "Number", "Person",
"Tense", "VerbForm", "Voice",
)
# The nine-position tag distinguishes all seven Greek tenses, which UD's
# ``Tense`` alone cannot: aorist, imperfect, perfect and pluperfect all read as
# ``Tense=Past``. Pairing Tense with Aspect keeps them apart in standard UD
# values, so the positional tag itself need not be published.
XPOS_TENSE = {
"p": (("Tense", "Pres"), ("Aspect", "Imp")), # present
"i": (("Tense", "Past"), ("Aspect", "Imp")), # imperfect
"a": (("Tense", "Past"), ("Aspect", "Perf")), # aorist
"r": (("Tense", "Pres"), ("Aspect", "Perf")), # perfect
"l": (("Tense", "Pqp"), ("Aspect", "Perf")), # pluperfect
"f": (("Tense", "Fut"),), # future
"t": (("Tense", "Fut"), ("Aspect", "Perf")), # future perfect
}
# ``n``, ``p`` and ``g`` are not moods. They were the only record that a verb
# was non-finite, and FEATS lost it: 20,798 infinitives and participles carried
# no VerbForm at all, while others carried a non-standard ``Mood=Inf``.
XPOS_MOOD = {
"i": (("Mood", "Ind"), ("VerbForm", "Fin")),
"s": (("Mood", "Sub"), ("VerbForm", "Fin")),
"o": (("Mood", "Opt"), ("VerbForm", "Fin")),
"m": (("Mood", "Imp"), ("VerbForm", "Fin")),
"n": (("VerbForm", "Inf"),),
"p": (("VerbForm", "Part"),),
"g": (("VerbForm", "Ger"),),
}
# ``e`` is the medio-passive, whose form does not decide between middle and
# passive; FEATS flattened it onto ``Mid`` alongside the true middle ``m``.
XPOS_VOICE = {
"a": "Act", "p": "Pass", "m": "Mid", "e": "Mid,Pass",
}
# ``c`` is the common gender, which only some projects tag. It varied
# twenty-six times more between annotators than between authors, so it is not
# published: those tokens simply carry no Gender.
XPOS_GENDER = {"m": "Masc", "f": "Fem", "n": "Neut"}
UNPUBLISHED_FEATS = frozenset({"Gender=Com"})
# Shared dependency inventory. Relations are merged wherever the projects
# express one analysis with different labels: ``det`` joins the attributive
# bucket because the AGDT lineage annotates the article as an attribute, and
# ``cc``/``cop``/``aux`` join the functional bucket because native schemes
# never produce them.
CORE_DEPREL = {
"root": "root",
"nsubj": "nsubj", "csubj": "nsubj",
"obj": "obj", "iobj": "obj",
"ccomp": "ccomp", "xcomp": "ccomp",
"obl": "obl",
# ``appos`` is merged away: whether a nominal is an apposition or an
# ordinary modifier is an analytic preference, and it varied twelve times
# more between two annotators of one author than between authors.
"nmod": "nmod", "amod": "nmod", "nummod": "nmod", "det": "nmod",
"appos": "nmod",
# The Greek particles are the same tokens everywhere; UD Perseus files them
# as adverbs and the AGDT lineage as discourse markers, at rates differing
# forty-fold while their sum agrees. Merging the two costs a distinction
# the projects do not share, and which UPOS already stopped drawing when
# PART, CCONJ, SCONJ and ADV were merged.
"advmod": "advmod", "acl": "advmod", "advcl": "advmod",
"discourse": "advmod", "dislocated": "advmod",
"case": "case", "mark": "case", "cc": "case", "cop": "case", "aux": "case",
"conj": "conj",
# ``vocative`` carried no authorial signal at all — it did not vary between
# sixteen authors of one project — while varying between annotators of one
# author. FEATS ``Case=Voc`` identifies vocatives exactly, so the relation
# was redundant as well as leaky.
"vocative": "dep",
"punct": "punct",
}
CORE_DEPRELS = frozenset(CORE_DEPREL.values()) | {"dep"}
def core_deprel(relation: str) -> str:
"""Collapse a relation onto the inventory every source project shares."""
base = (relation or "dep").split(":", 1)[0].lower()
return CORE_DEPREL.get(base, "dep")
def core_feats(feats: str) -> str:
"""Retain only the morphological features in the shared inventory."""
if not feats or feats == "_":
return "_"
retained = [
item for item in feats.split("|")
if item.split("=", 1)[0] in CORE_FEATS and item not in UNPUBLISHED_FEATS
]
return "|".join(sorted(retained)) or "_"
def canonical_feats(xpos: str, feats: str) -> str:
"""Return the one published morphological analysis of a token.
XPOS and FEATS each carried distinctions the other lost, and disagreed
with each other: the positional tag alone separated the Greek tenses and
the medio-passive, while FEATS alone recorded ambiguous genders such as
``Masc,Neut``. Publishing both invited them to drift further apart, so the
positional tag is folded in here and then dropped.
Tense, Aspect, Mood, VerbForm and Voice are taken from the normalized
XPOS, which makes them uniform across source projects rather than
inherited from whichever project annotated the sentence. Gender and the
remaining features keep their FEATS values, which are the finer of the two.
"""
parsed = dict(
item.split("=", 1) for item in feats.split("|")
if feats and feats != "_" and "=" in item
)
derived = {
key: value for key in ("Case", "Degree", "Gender", "Number", "Person")
if (value := parsed.get(key)) is not None
and f"{key}={value}" not in UNPUBLISHED_FEATS
}
if not xpos or xpos == "_":
return core_feats("|".join(f"{k}={v}" for k, v in sorted(derived.items())))
for slot, table in ((3, XPOS_TENSE), (4, XPOS_MOOD)):
for key, value in table.get(xpos[slot], ()):
derived[key] = value
voice = XPOS_VOICE.get(xpos[5])
if voice is not None:
derived["Voice"] = voice
if "Gender" not in derived and xpos[6] in XPOS_GENDER:
derived["Gender"] = XPOS_GENDER[xpos[6]]
# A tag whose slot was blank still keeps whatever FEATS recorded, so the
# pluperfects and participles the tag missed are not lost either.
for key in ("Tense", "Mood", "Voice"):
if key not in derived and key in parsed and parsed[key] not in {"Inf", "Part"}:
derived[key] = parsed[key]
if parsed.get("Mood") in {"Inf", "Part"} and "VerbForm" not in derived:
derived["VerbForm"] = parsed["Mood"]
return "|".join(f"{key}={derived[key]}" for key in sorted(derived)) or "_"
def core_xpos(xpos: str) -> str:
"""Merge the part-of-speech position onto the shared inventory."""
if not xpos or xpos == "_":
return xpos
if len(xpos) != 9:
raise ValueError(f"XPOS must have exactly nine positions, got {xpos!r}")
return CORE_XPOS_POS.get(xpos[0], "x") + xpos[1:]
def core_upos(xpos: str) -> str:
"""Derive UPOS from the normalized XPOS so both columns share one scheme."""
if not xpos or xpos == "_":
return "X"
return CORE_XPOS_TO_UPOS.get(CORE_XPOS_POS.get(xpos[0], "x"), "X")
|