File size: 4,423 Bytes
8247f19 | 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 | diff --git a/nltk/tokenize/punkt.py b/nltk/tokenize/punkt.py
index a08ff4c90..54937b9ec 100644
--- a/nltk/tokenize/punkt.py
+++ b/nltk/tokenize/punkt.py
@@ -266,7 +266,6 @@ class PunktLanguageVars:
return self._word_tokenizer_re().findall(s)
_period_context_fmt = r"""
- \S* # some word material
%(SentEndChars)s # a potential sentence ending
(?=(?P<after_tok>
%(NonWord)s # either other punctuation
@@ -1284,8 +1283,7 @@ class PunktSentenceTokenizer(PunktBaseClass, TokenizerI):
See format_debug_decision() to help make this output readable.
"""
- for match in self._lang_vars.period_context_re().finditer(text):
- decision_text = match.group() + match.group("after_tok")
+ for match, decision_text in self._match_potential_end_contexts(text):
tokens = self._tokenize_words(decision_text)
tokens = list(self._annotate_first_pass(tokens))
while tokens and not tokens[0].tok.endswith(self._lang_vars.sent_end_chars):
@@ -1333,10 +1331,68 @@ class PunktSentenceTokenizer(PunktBaseClass, TokenizerI):
"""
return [text[s:e] for s, e in self.span_tokenize(text, realign_boundaries)]
+ def _match_potential_end_contexts(self, text):
+ """
+ Given a text, find the matches of potential sentence breaks,
+ alongside the contexts surrounding these sentence breaks.
+
+ Since the fix for the ReDOS discovered in issue #2866, we no longer match
+ the word before a potential end of sentence token. Instead, we use a separate
+ regex for this. As a consequence, `finditer`'s desire to find non-overlapping
+ matches no longer aids us in finding the single longest match.
+ Where previously, we could use::
+
+ >>> pst = PunktSentenceTokenizer()
+ >>> text = "Very bad acting!!! I promise."
+ >>> list(pst._lang_vars.period_context_re().finditer(text)) # doctest: +SKIP
+ [<re.Match object; span=(9, 18), match='acting!!!'>]
+
+ Now we have to find the word before (i.e. 'acting') separately, and `finditer`
+ returns::
+
+ >>> pst = PunktSentenceTokenizer()
+ >>> text = "Very bad acting!!! I promise."
+ >>> list(pst._lang_vars.period_context_re().finditer(text)) # doctest: +NORMALIZE_WHITESPACE
+ [<re.Match object; span=(15, 16), match='!'>,
+ <re.Match object; span=(16, 17), match='!'>,
+ <re.Match object; span=(17, 18), match='!'>]
+
+ So, we need to find the word before the match from right to left, and then manually remove
+ the overlaps. That is what this method does::
+
+ >>> pst = PunktSentenceTokenizer()
+ >>> text = "Very bad acting!!! I promise."
+ >>> pst._match_potential_end_contexts(text)
+ [(<re.Match object; span=(17, 18), match='!'>, 'acting!!! I')]
+
+ :param text: String of one or more sentences
+ :type text: str
+ :return: List of match-context tuples.
+ :rtype: List[Tuple[re.Match, str]]
+ """
+ before_words = {}
+ matches = []
+ for match in reversed(list(self._lang_vars.period_context_re().finditer(text))):
+ # Ignore matches that have already been captured by matches to the right of this match
+ if matches and match.end() > before_start:
+ continue
+ # Find the word before the current match
+ split = text[: match.start()].rsplit(maxsplit=1)
+ before_start = len(split[0]) if len(split) == 2 else 0
+ before_words[match] = split[-1]
+ matches.append(match)
+
+ return [
+ (
+ match,
+ before_words[match] + match.group() + match.group("after_tok"),
+ )
+ for match in matches[::-1]
+ ]
+
def _slices_from_text(self, text):
last_break = 0
- for match in self._lang_vars.period_context_re().finditer(text):
- context = match.group() + match.group("after_tok")
+ for match, context in self._match_potential_end_contexts(text):
if self.text_contains_sentbreak(context):
yield slice(last_break, match.end())
if match.group("next_tok"):
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