Source code for nltk.tokenize.treebank

# Natural Language Toolkit: Tokenizers
#
# Copyright (C) 2001-2020 NLTK Project
# Author: Edward Loper <edloper@gmail.com>
#         Michael Heilman <mheilman@cmu.edu> (re-port from http://www.cis.upenn.edu/~treebank/tokenizer.sed)
#
# URL: <http://nltk.sourceforge.net>
# For license information, see LICENSE.TXT

r"""

Penn Treebank Tokenizer

The Treebank tokenizer uses regular expressions to tokenize text as in Penn Treebank.
This implementation is a port of the tokenizer sed script written by Robert McIntyre
and available at http://www.cis.upenn.edu/~treebank/tokenizer.sed.
"""

import re
from nltk.tokenize.api import TokenizerI
from nltk.tokenize.util import align_tokens
from nltk.tokenize.destructive import MacIntyreContractions


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