You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
237 lines
8.3 KiB
Python
237 lines
8.3 KiB
Python
# Natural Language Toolkit: Parser Utility Functions
|
|
#
|
|
# Author: Ewan Klein <ewan@inf.ed.ac.uk>
|
|
#
|
|
# Copyright (C) 2001-2019 NLTK Project
|
|
# URL: <http://nltk.org/>
|
|
# For license information, see LICENSE.TXT
|
|
|
|
|
|
"""
|
|
Utility functions for parsers.
|
|
"""
|
|
from __future__ import print_function
|
|
|
|
from nltk.grammar import CFG, FeatureGrammar, PCFG
|
|
from nltk.data import load
|
|
|
|
from nltk.parse.chart import Chart, ChartParser
|
|
from nltk.parse.pchart import InsideChartParser
|
|
from nltk.parse.featurechart import FeatureChart, FeatureChartParser
|
|
|
|
|
|
def load_parser(
|
|
grammar_url, trace=0, parser=None, chart_class=None, beam_size=0, **load_args
|
|
):
|
|
"""
|
|
Load a grammar from a file, and build a parser based on that grammar.
|
|
The parser depends on the grammar format, and might also depend
|
|
on properties of the grammar itself.
|
|
|
|
The following grammar formats are currently supported:
|
|
- ``'cfg'`` (CFGs: ``CFG``)
|
|
- ``'pcfg'`` (probabilistic CFGs: ``PCFG``)
|
|
- ``'fcfg'`` (feature-based CFGs: ``FeatureGrammar``)
|
|
|
|
:type grammar_url: str
|
|
:param grammar_url: A URL specifying where the grammar is located.
|
|
The default protocol is ``"nltk:"``, which searches for the file
|
|
in the the NLTK data package.
|
|
:type trace: int
|
|
:param trace: The level of tracing that should be used when
|
|
parsing a text. ``0`` will generate no tracing output;
|
|
and higher numbers will produce more verbose tracing output.
|
|
:param parser: The class used for parsing; should be ``ChartParser``
|
|
or a subclass.
|
|
If None, the class depends on the grammar format.
|
|
:param chart_class: The class used for storing the chart;
|
|
should be ``Chart`` or a subclass.
|
|
Only used for CFGs and feature CFGs.
|
|
If None, the chart class depends on the grammar format.
|
|
:type beam_size: int
|
|
:param beam_size: The maximum length for the parser's edge queue.
|
|
Only used for probabilistic CFGs.
|
|
:param load_args: Keyword parameters used when loading the grammar.
|
|
See ``data.load`` for more information.
|
|
"""
|
|
grammar = load(grammar_url, **load_args)
|
|
if not isinstance(grammar, CFG):
|
|
raise ValueError("The grammar must be a CFG, " "or a subclass thereof.")
|
|
if isinstance(grammar, PCFG):
|
|
if parser is None:
|
|
parser = InsideChartParser
|
|
return parser(grammar, trace=trace, beam_size=beam_size)
|
|
|
|
elif isinstance(grammar, FeatureGrammar):
|
|
if parser is None:
|
|
parser = FeatureChartParser
|
|
if chart_class is None:
|
|
chart_class = FeatureChart
|
|
return parser(grammar, trace=trace, chart_class=chart_class)
|
|
|
|
else: # Plain CFG.
|
|
if parser is None:
|
|
parser = ChartParser
|
|
if chart_class is None:
|
|
chart_class = Chart
|
|
return parser(grammar, trace=trace, chart_class=chart_class)
|
|
|
|
|
|
def taggedsent_to_conll(sentence):
|
|
"""
|
|
A module to convert a single POS tagged sentence into CONLL format.
|
|
|
|
>>> from nltk import word_tokenize, pos_tag
|
|
>>> text = "This is a foobar sentence."
|
|
>>> for line in taggedsent_to_conll(pos_tag(word_tokenize(text))):
|
|
... print(line, end="")
|
|
1 This _ DT DT _ 0 a _ _
|
|
2 is _ VBZ VBZ _ 0 a _ _
|
|
3 a _ DT DT _ 0 a _ _
|
|
4 foobar _ JJ JJ _ 0 a _ _
|
|
5 sentence _ NN NN _ 0 a _ _
|
|
6 . _ . . _ 0 a _ _
|
|
|
|
:param sentence: A single input sentence to parse
|
|
:type sentence: list(tuple(str, str))
|
|
:rtype: iter(str)
|
|
:return: a generator yielding a single sentence in CONLL format.
|
|
"""
|
|
for (i, (word, tag)) in enumerate(sentence, start=1):
|
|
input_str = [str(i), word, '_', tag, tag, '_', '0', 'a', '_', '_']
|
|
input_str = "\t".join(input_str) + "\n"
|
|
yield input_str
|
|
|
|
|
|
def taggedsents_to_conll(sentences):
|
|
"""
|
|
A module to convert the a POS tagged document stream
|
|
(i.e. list of list of tuples, a list of sentences) and yield lines
|
|
in CONLL format. This module yields one line per word and two newlines
|
|
for end of sentence.
|
|
|
|
>>> from nltk import word_tokenize, sent_tokenize, pos_tag
|
|
>>> text = "This is a foobar sentence. Is that right?"
|
|
>>> sentences = [pos_tag(word_tokenize(sent)) for sent in sent_tokenize(text)]
|
|
>>> for line in taggedsents_to_conll(sentences):
|
|
... if line:
|
|
... print(line, end="")
|
|
1 This _ DT DT _ 0 a _ _
|
|
2 is _ VBZ VBZ _ 0 a _ _
|
|
3 a _ DT DT _ 0 a _ _
|
|
4 foobar _ JJ JJ _ 0 a _ _
|
|
5 sentence _ NN NN _ 0 a _ _
|
|
6 . _ . . _ 0 a _ _
|
|
<BLANKLINE>
|
|
<BLANKLINE>
|
|
1 Is _ VBZ VBZ _ 0 a _ _
|
|
2 that _ IN IN _ 0 a _ _
|
|
3 right _ NN NN _ 0 a _ _
|
|
4 ? _ . . _ 0 a _ _
|
|
<BLANKLINE>
|
|
<BLANKLINE>
|
|
|
|
:param sentences: Input sentences to parse
|
|
:type sentence: list(list(tuple(str, str)))
|
|
:rtype: iter(str)
|
|
:return: a generator yielding sentences in CONLL format.
|
|
"""
|
|
for sentence in sentences:
|
|
for input_str in taggedsent_to_conll(sentence):
|
|
yield input_str
|
|
yield '\n\n'
|
|
|
|
|
|
######################################################################
|
|
# { Test Suites
|
|
######################################################################
|
|
|
|
|
|
class TestGrammar(object):
|
|
"""
|
|
Unit tests for CFG.
|
|
"""
|
|
|
|
def __init__(self, grammar, suite, accept=None, reject=None):
|
|
self.test_grammar = grammar
|
|
|
|
self.cp = load_parser(grammar, trace=0)
|
|
self.suite = suite
|
|
self._accept = accept
|
|
self._reject = reject
|
|
|
|
def run(self, show_trees=False):
|
|
"""
|
|
Sentences in the test suite are divided into two classes:
|
|
- grammatical (``accept``) and
|
|
- ungrammatical (``reject``).
|
|
If a sentence should parse accordng to the grammar, the value of
|
|
``trees`` will be a non-empty list. If a sentence should be rejected
|
|
according to the grammar, then the value of ``trees`` will be None.
|
|
"""
|
|
for test in self.suite:
|
|
print(test['doc'] + ":", end=' ')
|
|
for key in ['accept', 'reject']:
|
|
for sent in test[key]:
|
|
tokens = sent.split()
|
|
trees = list(self.cp.parse(tokens))
|
|
if show_trees and trees:
|
|
print()
|
|
print(sent)
|
|
for tree in trees:
|
|
print(tree)
|
|
if key == 'accept':
|
|
if trees == []:
|
|
raise ValueError("Sentence '%s' failed to parse'" % sent)
|
|
else:
|
|
accepted = True
|
|
else:
|
|
if trees:
|
|
raise ValueError("Sentence '%s' received a parse'" % sent)
|
|
else:
|
|
rejected = True
|
|
if accepted and rejected:
|
|
print("All tests passed!")
|
|
|
|
|
|
def extract_test_sentences(string, comment_chars="#%;", encoding=None):
|
|
"""
|
|
Parses a string with one test sentence per line.
|
|
Lines can optionally begin with:
|
|
- a bool, saying if the sentence is grammatical or not, or
|
|
- an int, giving the number of parse trees is should have,
|
|
The result information is followed by a colon, and then the sentence.
|
|
Empty lines and lines beginning with a comment char are ignored.
|
|
|
|
:return: a list of tuple of sentences and expected results,
|
|
where a sentence is a list of str,
|
|
and a result is None, or bool, or int
|
|
|
|
:param comment_chars: ``str`` of possible comment characters.
|
|
:param encoding: the encoding of the string, if it is binary
|
|
"""
|
|
if encoding is not None:
|
|
string = string.decode(encoding)
|
|
sentences = []
|
|
for sentence in string.split('\n'):
|
|
if sentence == '' or sentence[0] in comment_chars:
|
|
continue
|
|
split_info = sentence.split(':', 1)
|
|
result = None
|
|
if len(split_info) == 2:
|
|
if split_info[0] in ['True', 'true', 'False', 'false']:
|
|
result = split_info[0] in ['True', 'true']
|
|
sentence = split_info[1]
|
|
else:
|
|
result = int(split_info[0])
|
|
sentence = split_info[1]
|
|
tokens = sentence.split()
|
|
if tokens == []:
|
|
continue
|
|
sentences += [(tokens, result)]
|
|
return sentences
|
|
|
|
|
|
# nose thinks it is a test
|
|
extract_test_sentences.__test__ = False
|