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# Natural Language Toolkit: Tokenizers
#
# Copyright (C) 2001-2019 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
class MacIntyreContractions:
"""
List of contractions adapted from Robert MacIntyre's tokenizer.
"""
CONTRACTIONS2 = [
r"(?i)\b(can)(?#X)(not)\b",
r"(?i)\b(d)(?#X)('ye)\b",
r"(?i)\b(gim)(?#X)(me)\b",
r"(?i)\b(gon)(?#X)(na)\b",
r"(?i)\b(got)(?#X)(ta)\b",
r"(?i)\b(lem)(?#X)(me)\b",
r"(?i)\b(mor)(?#X)('n)\b",
r"(?i)\b(wan)(?#X)(na)\s",
]
CONTRACTIONS3 = [r"(?i) ('t)(?#X)(is)\b", r"(?i) ('t)(?#X)(was)\b"]
CONTRACTIONS4 = [r"(?i)\b(whad)(dd)(ya)\b", r"(?i)\b(wha)(t)(cha)\b"]
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))
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()
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
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'\"'),
]
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()
def detokenize(self, tokens, convert_parentheses=False):
""" Duck-typing the abstract *tokenize()*."""
return self.tokenize(tokens, convert_parentheses)