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369 lines
15 KiB
Python
369 lines
15 KiB
Python
# Natural Language Toolkit: Tokenizers
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#
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# Copyright (C) 2001-2020 NLTK Project
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# Author: Edward Loper <edloper@gmail.com>
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# Michael Heilman <mheilman@cmu.edu> (re-port from http://www.cis.upenn.edu/~treebank/tokenizer.sed)
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#
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# URL: <http://nltk.sourceforge.net>
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# For license information, see LICENSE.TXT
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r"""
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Penn Treebank Tokenizer
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The Treebank tokenizer uses regular expressions to tokenize text as in Penn Treebank.
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This implementation is a port of the tokenizer sed script written by Robert McIntyre
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and available at http://www.cis.upenn.edu/~treebank/tokenizer.sed.
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"""
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import re
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from nltk.tokenize.api import TokenizerI
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from nltk.tokenize.util import align_tokens
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from nltk.tokenize.destructive import MacIntyreContractions
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class TreebankWordTokenizer(TokenizerI):
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"""
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The Treebank tokenizer uses regular expressions to tokenize text as in Penn Treebank.
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This is the method that is invoked by ``word_tokenize()``. It assumes that the
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text has already been segmented into sentences, e.g. using ``sent_tokenize()``.
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This tokenizer performs the following steps:
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- split standard contractions, e.g. ``don't`` -> ``do n't`` and ``they'll`` -> ``they 'll``
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- treat most punctuation characters as separate tokens
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- split off commas and single quotes, when followed by whitespace
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- separate periods that appear at the end of line
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>>> from nltk.tokenize import TreebankWordTokenizer
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>>> s = '''Good muffins cost $3.88\\nin New York. Please buy me\\ntwo of them.\\nThanks.'''
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>>> TreebankWordTokenizer().tokenize(s)
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['Good', 'muffins', 'cost', '$', '3.88', 'in', 'New', 'York.', 'Please', 'buy', 'me', 'two', 'of', 'them.', 'Thanks', '.']
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>>> s = "They'll save and invest more."
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>>> TreebankWordTokenizer().tokenize(s)
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['They', "'ll", 'save', 'and', 'invest', 'more', '.']
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>>> s = "hi, my name can't hello,"
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>>> TreebankWordTokenizer().tokenize(s)
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['hi', ',', 'my', 'name', 'ca', "n't", 'hello', ',']
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"""
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# starting quotes
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STARTING_QUOTES = [
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(re.compile(r"^\""), r"``"),
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(re.compile(r"(``)"), r" \1 "),
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(re.compile(r"([ \(\[{<])(\"|\'{2})"), r"\1 `` "),
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]
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# punctuation
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PUNCTUATION = [
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(re.compile(r"([:,])([^\d])"), r" \1 \2"),
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(re.compile(r"([:,])$"), r" \1 "),
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(re.compile(r"\.\.\."), r" ... "),
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(re.compile(r"[;@#$%&]"), r" \g<0> "),
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(
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re.compile(r'([^\.])(\.)([\]\)}>"\']*)\s*$'),
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r"\1 \2\3 ",
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), # Handles the final period.
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(re.compile(r"[?!]"), r" \g<0> "),
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(re.compile(r"([^'])' "), r"\1 ' "),
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]
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# Pads parentheses
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PARENS_BRACKETS = (re.compile(r"[\]\[\(\)\{\}\<\>]"), r" \g<0> ")
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# Optionally: Convert parentheses, brackets and converts them to PTB symbols.
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CONVERT_PARENTHESES = [
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(re.compile(r"\("), "-LRB-"),
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(re.compile(r"\)"), "-RRB-"),
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(re.compile(r"\["), "-LSB-"),
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(re.compile(r"\]"), "-RSB-"),
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(re.compile(r"\{"), "-LCB-"),
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(re.compile(r"\}"), "-RCB-"),
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]
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DOUBLE_DASHES = (re.compile(r"--"), r" -- ")
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# ending quotes
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ENDING_QUOTES = [
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(re.compile(r'"'), " '' "),
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(re.compile(r"(\S)(\'\')"), r"\1 \2 "),
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(re.compile(r"([^' ])('[sS]|'[mM]|'[dD]|') "), r"\1 \2 "),
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(re.compile(r"([^' ])('ll|'LL|'re|'RE|'ve|'VE|n't|N'T) "), r"\1 \2 "),
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]
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# List of contractions adapted from Robert MacIntyre's tokenizer.
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_contractions = MacIntyreContractions()
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CONTRACTIONS2 = list(map(re.compile, _contractions.CONTRACTIONS2))
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CONTRACTIONS3 = list(map(re.compile, _contractions.CONTRACTIONS3))
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def tokenize(self, text, convert_parentheses=False, return_str=False):
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for regexp, substitution in self.STARTING_QUOTES:
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text = regexp.sub(substitution, text)
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for regexp, substitution in self.PUNCTUATION:
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text = regexp.sub(substitution, text)
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# Handles parentheses.
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regexp, substitution = self.PARENS_BRACKETS
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text = regexp.sub(substitution, text)
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# Optionally convert parentheses
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if convert_parentheses:
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for regexp, substitution in self.CONVERT_PARENTHESES:
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text = regexp.sub(substitution, text)
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# Handles double dash.
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regexp, substitution = self.DOUBLE_DASHES
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text = regexp.sub(substitution, text)
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# add extra space to make things easier
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text = " " + text + " "
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for regexp, substitution in self.ENDING_QUOTES:
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text = regexp.sub(substitution, text)
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for regexp in self.CONTRACTIONS2:
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text = regexp.sub(r" \1 \2 ", text)
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for regexp in self.CONTRACTIONS3:
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text = regexp.sub(r" \1 \2 ", text)
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# We are not using CONTRACTIONS4 since
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# they are also commented out in the SED scripts
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# for regexp in self._contractions.CONTRACTIONS4:
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# text = regexp.sub(r' \1 \2 \3 ', text)
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return text if return_str else text.split()
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def span_tokenize(self, text):
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"""
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Uses the post-hoc nltk.tokens.align_tokens to return the offset spans.
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>>> from nltk.tokenize import TreebankWordTokenizer
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>>> s = '''Good muffins cost $3.88\\nin New (York). Please (buy) me\\ntwo of them.\\n(Thanks).'''
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>>> expected = [(0, 4), (5, 12), (13, 17), (18, 19), (19, 23),
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... (24, 26), (27, 30), (31, 32), (32, 36), (36, 37), (37, 38),
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... (40, 46), (47, 48), (48, 51), (51, 52), (53, 55), (56, 59),
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... (60, 62), (63, 68), (69, 70), (70, 76), (76, 77), (77, 78)]
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>>> list(TreebankWordTokenizer().span_tokenize(s)) == expected
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True
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>>> expected = ['Good', 'muffins', 'cost', '$', '3.88', 'in',
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... 'New', '(', 'York', ')', '.', 'Please', '(', 'buy', ')',
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... 'me', 'two', 'of', 'them.', '(', 'Thanks', ')', '.']
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>>> [s[start:end] for start, end in TreebankWordTokenizer().span_tokenize(s)] == expected
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True
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Additional example
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>>> from nltk.tokenize import TreebankWordTokenizer
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>>> s = '''I said, "I'd like to buy some ''good muffins" which cost $3.88\\n each in New (York)."'''
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>>> expected = [(0, 1), (2, 6), (6, 7), (8, 9), (9, 10), (10, 12),
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... (13, 17), (18, 20), (21, 24), (25, 29), (30, 32), (32, 36),
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... (37, 44), (44, 45), (46, 51), (52, 56), (57, 58), (58, 62),
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... (64, 68), (69, 71), (72, 75), (76, 77), (77, 81), (81, 82),
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... (82, 83), (83, 84)]
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>>> list(TreebankWordTokenizer().span_tokenize(s)) == expected
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True
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>>> expected = ['I', 'said', ',', '"', 'I', "'d", 'like', 'to',
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... 'buy', 'some', "''", "good", 'muffins', '"', 'which', 'cost',
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... '$', '3.88', 'each', 'in', 'New', '(', 'York', ')', '.', '"']
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>>> [s[start:end] for start, end in TreebankWordTokenizer().span_tokenize(s)] == expected
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True
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"""
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raw_tokens = self.tokenize(text)
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# Convert converted quotes back to original double quotes
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# Do this only if original text contains double quote(s) or double
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# single-quotes (because '' might be transformed to `` if it is
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# treated as starting quotes).
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if ('"' in text) or ("''" in text):
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# Find double quotes and converted quotes
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matched = [m.group() for m in re.finditer(r"``|'{2}|\"", text)]
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# Replace converted quotes back to double quotes
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tokens = [
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matched.pop(0) if tok in ['"', "``", "''"] else tok
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for tok in raw_tokens
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]
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else:
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tokens = raw_tokens
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for tok in align_tokens(tokens, text):
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yield tok
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class TreebankWordDetokenizer(TokenizerI):
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"""
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The Treebank detokenizer uses the reverse regex operations corresponding to
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the Treebank tokenizer's regexes.
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Note:
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- There're additional assumption mades when undoing the padding of [;@#$%&]
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punctuation symbols that isn't presupposed in the TreebankTokenizer.
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- There're additional regexes added in reversing the parentheses tokenization,
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- the r'([\]\)\}\>])\s([:;,.])' removes the additional right padding added
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to the closing parentheses precedding [:;,.].
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- It's not possible to return the original whitespaces as they were because
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there wasn't explicit records of where '\n', '\t' or '\s' were removed at
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the text.split() operation.
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>>> from nltk.tokenize.treebank import TreebankWordTokenizer, TreebankWordDetokenizer
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>>> s = '''Good muffins cost $3.88\\nin New York. Please buy me\\ntwo of them.\\nThanks.'''
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>>> d = TreebankWordDetokenizer()
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>>> t = TreebankWordTokenizer()
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>>> toks = t.tokenize(s)
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>>> d.detokenize(toks)
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'Good muffins cost $3.88 in New York. Please buy me two of them. Thanks.'
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The MXPOST parentheses substitution can be undone using the `convert_parentheses`
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parameter:
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>>> s = '''Good muffins cost $3.88\\nin New (York). Please (buy) me\\ntwo of them.\\n(Thanks).'''
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>>> expected_tokens = ['Good', 'muffins', 'cost', '$', '3.88', 'in',
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... 'New', '-LRB-', 'York', '-RRB-', '.', 'Please', '-LRB-', 'buy',
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... '-RRB-', 'me', 'two', 'of', 'them.', '-LRB-', 'Thanks', '-RRB-', '.']
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>>> expected_tokens == t.tokenize(s, convert_parentheses=True)
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True
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>>> expected_detoken = 'Good muffins cost $3.88 in New (York). Please (buy) me two of them. (Thanks).'
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>>> expected_detoken == d.detokenize(t.tokenize(s, convert_parentheses=True), convert_parentheses=True)
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True
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During tokenization it's safe to add more spaces but during detokenization,
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simply undoing the padding doesn't really help.
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- During tokenization, left and right pad is added to [!?], when
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detokenizing, only left shift the [!?] is needed.
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Thus (re.compile(r'\s([?!])'), r'\g<1>')
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- During tokenization [:,] are left and right padded but when detokenizing,
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only left shift is necessary and we keep right pad after comma/colon
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if the string after is a non-digit.
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Thus (re.compile(r'\s([:,])\s([^\d])'), r'\1 \2')
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>>> from nltk.tokenize.treebank import TreebankWordDetokenizer
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>>> toks = ['hello', ',', 'i', 'ca', "n't", 'feel', 'my', 'feet', '!', 'Help', '!', '!']
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>>> twd = TreebankWordDetokenizer()
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>>> twd.detokenize(toks)
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"hello, i can't feel my feet! Help!!"
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>>> toks = ['hello', ',', 'i', "can't", 'feel', ';', 'my', 'feet', '!',
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... 'Help', '!', '!', 'He', 'said', ':', 'Help', ',', 'help', '?', '!']
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>>> twd.detokenize(toks)
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"hello, i can't feel; my feet! Help!! He said: Help, help?!"
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"""
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_contractions = MacIntyreContractions()
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CONTRACTIONS2 = [
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re.compile(pattern.replace("(?#X)", "\s"))
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for pattern in _contractions.CONTRACTIONS2
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]
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CONTRACTIONS3 = [
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re.compile(pattern.replace("(?#X)", "\s"))
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for pattern in _contractions.CONTRACTIONS3
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]
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# ending quotes
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ENDING_QUOTES = [
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(re.compile(r"([^' ])\s('ll|'LL|'re|'RE|'ve|'VE|n't|N'T) "), r"\1\2 "),
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(re.compile(r"([^' ])\s('[sS]|'[mM]|'[dD]|') "), r"\1\2 "),
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(re.compile(r"(\S)(\'\')"), r"\1\2 "),
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(re.compile(r" '' "), '"'),
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]
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# Handles double dashes
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DOUBLE_DASHES = (re.compile(r" -- "), r"--")
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# Optionally: Convert parentheses, brackets and converts them from PTB symbols.
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CONVERT_PARENTHESES = [
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(re.compile("-LRB-"), "("),
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(re.compile("-RRB-"), ")"),
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(re.compile("-LSB-"), "["),
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(re.compile("-RSB-"), "]"),
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(re.compile("-LCB-"), "{"),
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(re.compile("-RCB-"), "}"),
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]
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# Undo padding on parentheses.
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PARENS_BRACKETS = [
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(re.compile(r"\s([\[\(\{\<])\s"), r" \g<1>"),
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(re.compile(r"\s([\]\)\}\>])\s"), r"\g<1> "),
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(re.compile(r"([\]\)\}\>])\s([:;,.])"), r"\1\2"),
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]
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# punctuation
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PUNCTUATION = [
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(re.compile(r"([^'])\s'\s"), r"\1' "),
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(re.compile(r"\s([?!])"), r"\g<1>"), # Strip left pad for [?!]
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# (re.compile(r'\s([?!])\s'), r'\g<1>'),
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(re.compile(r'([^\.])\s(\.)([\]\)}>"\']*)\s*$'), r"\1\2\3"),
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# When tokenizing, [;@#$%&] are padded with whitespace regardless of
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# whether there are spaces before or after them.
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# But during detokenization, we need to distinguish between left/right
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# pad, so we split this up.
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(re.compile(r"\s([#$])\s"), r" \g<1>"), # Left pad.
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(re.compile(r"\s([;%])\s"), r"\g<1> "), # Right pad.
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(re.compile(r"\s([&*])\s"), r" \g<1> "), # Unknown pad.
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(re.compile(r"\s\.\.\.\s"), r"..."),
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(re.compile(r"\s([:,])\s$"), r"\1"),
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(
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re.compile(r"\s([:,])\s([^\d])"),
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r"\1 \2",
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) # Keep right pad after comma/colon before non-digits.
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# (re.compile(r'\s([:,])\s([^\d])'), r'\1\2')
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]
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# starting quotes
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STARTING_QUOTES = [
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(re.compile(r"([ (\[{<])\s``"), r'\1"'),
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(re.compile(r"\s(``)\s"), r"\1"),
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(re.compile(r"^``"), r"\""),
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]
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def tokenize(self, tokens, convert_parentheses=False):
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"""
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Treebank detokenizer, created by undoing the regexes from
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the TreebankWordTokenizer.tokenize.
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:param tokens: A list of strings, i.e. tokenized text.
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:type tokens: list(str)
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:return: str
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"""
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text = " ".join(tokens)
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# Reverse the contractions regexes.
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# Note: CONTRACTIONS4 are not used in tokenization.
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for regexp in self.CONTRACTIONS3:
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text = regexp.sub(r"\1\2", text)
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for regexp in self.CONTRACTIONS2:
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text = regexp.sub(r"\1\2", text)
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# Reverse the regexes applied for ending quotes.
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for regexp, substitution in self.ENDING_QUOTES:
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text = regexp.sub(substitution, text)
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# Undo the space padding.
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text = text.strip()
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# Reverse the padding on double dashes.
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regexp, substitution = self.DOUBLE_DASHES
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text = regexp.sub(substitution, text)
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if convert_parentheses:
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for regexp, substitution in self.CONVERT_PARENTHESES:
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text = regexp.sub(substitution, text)
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# Reverse the padding regexes applied for parenthesis/brackets.
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for regexp, substitution in self.PARENS_BRACKETS:
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text = regexp.sub(substitution, text)
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# Reverse the regexes applied for punctuations.
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for regexp, substitution in self.PUNCTUATION:
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text = regexp.sub(substitution, text)
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# Reverse the regexes applied for starting quotes.
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for regexp, substitution in self.STARTING_QUOTES:
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text = regexp.sub(substitution, text)
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return text.strip()
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def detokenize(self, tokens, convert_parentheses=False):
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""" Duck-typing the abstract *tokenize()*."""
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return self.tokenize(tokens, convert_parentheses)
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