322 lines
11 KiB
Python
322 lines
11 KiB
Python
|
# -*- coding: utf-8 -*-
|
||
|
|
# Natural Language Toolkit: Transformation-based learning
|
||
|
|
#
|
||
|
|
# Copyright (C) 2001-2018 NLTK Project
|
||
|
|
# Author: Marcus Uneson <marcus.uneson@gmail.com>
|
||
|
|
# based on previous (nltk2) version by
|
||
|
|
# Christopher Maloof, Edward Loper, Steven Bird
|
||
|
|
# URL: <http://nltk.org/>
|
||
|
|
# For license information, see LICENSE.TXT
|
||
|
|
|
||
|
|
from __future__ import print_function
|
||
|
|
from abc import ABCMeta, abstractmethod
|
||
|
|
from six import add_metaclass
|
||
|
|
|
||
|
|
from nltk.compat import python_2_unicode_compatible, unicode_repr
|
||
|
|
from nltk import jsontags
|
||
|
|
|
||
|
|
|
||
|
|
######################################################################
|
||
|
|
# Tag Rules
|
||
|
|
######################################################################
|
||
|
|
@add_metaclass(ABCMeta)
|
||
|
|
class TagRule(object):
|
||
|
|
"""
|
||
|
|
An interface for tag transformations on a tagged corpus, as
|
||
|
|
performed by tbl taggers. Each transformation finds all tokens
|
||
|
|
in the corpus that are tagged with a specific original tag and
|
||
|
|
satisfy a specific condition, and replaces their tags with a
|
||
|
|
replacement tag. For any given transformation, the original
|
||
|
|
tag, replacement tag, and condition are fixed. Conditions may
|
||
|
|
depend on the token under consideration, as well as any other
|
||
|
|
tokens in the corpus.
|
||
|
|
|
||
|
|
Tag rules must be comparable and hashable.
|
||
|
|
"""
|
||
|
|
|
||
|
|
def __init__(self, original_tag, replacement_tag):
|
||
|
|
|
||
|
|
self.original_tag = original_tag
|
||
|
|
"""The tag which this TagRule may cause to be replaced."""
|
||
|
|
|
||
|
|
self.replacement_tag = replacement_tag
|
||
|
|
"""The tag with which this TagRule may replace another tag."""
|
||
|
|
|
||
|
|
def apply(self, tokens, positions=None):
|
||
|
|
"""
|
||
|
|
Apply this rule at every position in positions where it
|
||
|
|
applies to the given sentence. I.e., for each position p
|
||
|
|
in *positions*, if *tokens[p]* is tagged with this rule's
|
||
|
|
original tag, and satisfies this rule's condition, then set
|
||
|
|
its tag to be this rule's replacement tag.
|
||
|
|
|
||
|
|
:param tokens: The tagged sentence
|
||
|
|
:type tokens: list(tuple(str, str))
|
||
|
|
:type positions: list(int)
|
||
|
|
:param positions: The positions where the transformation is to
|
||
|
|
be tried. If not specified, try it at all positions.
|
||
|
|
:return: The indices of tokens whose tags were changed by this
|
||
|
|
rule.
|
||
|
|
:rtype: int
|
||
|
|
"""
|
||
|
|
if positions is None:
|
||
|
|
positions = list(range(len(tokens)))
|
||
|
|
|
||
|
|
# Determine the indices at which this rule applies.
|
||
|
|
change = [i for i in positions if self.applies(tokens, i)]
|
||
|
|
|
||
|
|
# Make the changes. Note: this must be done in a separate
|
||
|
|
# step from finding applicable locations, since we don't want
|
||
|
|
# the rule to interact with itself.
|
||
|
|
for i in change:
|
||
|
|
tokens[i] = (tokens[i][0], self.replacement_tag)
|
||
|
|
|
||
|
|
return change
|
||
|
|
|
||
|
|
@abstractmethod
|
||
|
|
def applies(self, tokens, index):
|
||
|
|
"""
|
||
|
|
:return: True if the rule would change the tag of
|
||
|
|
``tokens[index]``, False otherwise
|
||
|
|
:rtype: bool
|
||
|
|
:param tokens: A tagged sentence
|
||
|
|
:type tokens: list(str)
|
||
|
|
:param index: The index to check
|
||
|
|
:type index: int
|
||
|
|
"""
|
||
|
|
|
||
|
|
# Rules must be comparable and hashable for the algorithm to work
|
||
|
|
def __eq__(self, other):
|
||
|
|
raise TypeError("Rules must implement __eq__()")
|
||
|
|
|
||
|
|
def __ne__(self, other):
|
||
|
|
raise TypeError("Rules must implement __ne__()")
|
||
|
|
|
||
|
|
def __hash__(self):
|
||
|
|
raise TypeError("Rules must implement __hash__()")
|
||
|
|
|
||
|
|
|
||
|
|
@python_2_unicode_compatible
|
||
|
|
@jsontags.register_tag
|
||
|
|
class Rule(TagRule):
|
||
|
|
"""
|
||
|
|
A Rule checks the current corpus position for a certain set of conditions;
|
||
|
|
if they are all fulfilled, the Rule is triggered, meaning that it
|
||
|
|
will change tag A to tag B. For other tags than A, nothing happens.
|
||
|
|
|
||
|
|
The conditions are parameters to the Rule instance. Each condition is a feature-value pair,
|
||
|
|
with a set of positions to check for the value of the corresponding feature.
|
||
|
|
Conceptually, the positions are joined by logical OR, and the feature set by logical AND.
|
||
|
|
|
||
|
|
More formally, the Rule is then applicable to the M{n}th token iff:
|
||
|
|
|
||
|
|
- The M{n}th token is tagged with the Rule's original tag; and
|
||
|
|
- For each (Feature(positions), M{value}) tuple:
|
||
|
|
- The value of Feature of at least one token in {n+p for p in positions}
|
||
|
|
is M{value}.
|
||
|
|
|
||
|
|
"""
|
||
|
|
|
||
|
|
json_tag = 'nltk.tbl.Rule'
|
||
|
|
|
||
|
|
def __init__(self, templateid, original_tag, replacement_tag, conditions):
|
||
|
|
"""
|
||
|
|
Construct a new Rule that changes a token's tag from
|
||
|
|
C{original_tag} to C{replacement_tag} if all of the properties
|
||
|
|
specified in C{conditions} hold.
|
||
|
|
|
||
|
|
@type templateid: string
|
||
|
|
@param templateid: the template id (a zero-padded string, '001' etc,
|
||
|
|
so it will sort nicely)
|
||
|
|
|
||
|
|
@type conditions: C{iterable} of C{Feature}
|
||
|
|
@param conditions: A list of Feature(positions),
|
||
|
|
each of which specifies that the property (computed by
|
||
|
|
Feature.extract_property()) of at least one
|
||
|
|
token in M{n} + p in positions is C{value}.
|
||
|
|
|
||
|
|
"""
|
||
|
|
TagRule.__init__(self, original_tag, replacement_tag)
|
||
|
|
self._conditions = conditions
|
||
|
|
self.templateid = templateid
|
||
|
|
|
||
|
|
def encode_json_obj(self):
|
||
|
|
return {
|
||
|
|
'templateid': self.templateid,
|
||
|
|
'original': self.original_tag,
|
||
|
|
'replacement': self.replacement_tag,
|
||
|
|
'conditions': self._conditions,
|
||
|
|
}
|
||
|
|
|
||
|
|
@classmethod
|
||
|
|
def decode_json_obj(cls, obj):
|
||
|
|
return cls(obj['templateid'], obj['original'], obj['replacement'], obj['conditions'])
|
||
|
|
|
||
|
|
def applies(self, tokens, index):
|
||
|
|
# Inherit docs from TagRule
|
||
|
|
|
||
|
|
# Does the given token have this Rule's "original tag"?
|
||
|
|
if tokens[index][1] != self.original_tag:
|
||
|
|
return False
|
||
|
|
|
||
|
|
# Check to make sure that every condition holds.
|
||
|
|
for (feature, val) in self._conditions:
|
||
|
|
|
||
|
|
# Look for *any* token that satisfies the condition.
|
||
|
|
for pos in feature.positions:
|
||
|
|
if not (0 <= index + pos < len(tokens)):
|
||
|
|
continue
|
||
|
|
if feature.extract_property(tokens, index+pos) == val:
|
||
|
|
break
|
||
|
|
else:
|
||
|
|
# No token satisfied the condition; return false.
|
||
|
|
return False
|
||
|
|
|
||
|
|
# Every condition checked out, so the Rule is applicable.
|
||
|
|
return True
|
||
|
|
|
||
|
|
def __eq__(self, other):
|
||
|
|
return (self is other or
|
||
|
|
(other is not None and
|
||
|
|
other.__class__ == self.__class__ and
|
||
|
|
self.original_tag == other.original_tag and
|
||
|
|
self.replacement_tag == other.replacement_tag and
|
||
|
|
self._conditions == other._conditions))
|
||
|
|
|
||
|
|
def __ne__(self, other):
|
||
|
|
return not (self == other)
|
||
|
|
|
||
|
|
def __hash__(self):
|
||
|
|
|
||
|
|
# Cache our hash value (justified by profiling.)
|
||
|
|
try:
|
||
|
|
return self.__hash
|
||
|
|
except AttributeError:
|
||
|
|
self.__hash = hash(repr(self))
|
||
|
|
return self.__hash
|
||
|
|
|
||
|
|
def __repr__(self):
|
||
|
|
# Cache the repr (justified by profiling -- this is used as
|
||
|
|
# a sort key when deterministic=True.)
|
||
|
|
try:
|
||
|
|
return self.__repr
|
||
|
|
except AttributeError:
|
||
|
|
self.__repr = (
|
||
|
|
"{0}('{1}', {2}, {3}, [{4}])".format(
|
||
|
|
self.__class__.__name__,
|
||
|
|
self.templateid,
|
||
|
|
unicode_repr(self.original_tag),
|
||
|
|
unicode_repr(self.replacement_tag),
|
||
|
|
|
||
|
|
# list(self._conditions) would be simpler but will not generate
|
||
|
|
# the same Rule.__repr__ in python 2 and 3 and thus break some tests
|
||
|
|
', '.join("({0},{1})".format(f, unicode_repr(v)) for (f, v) in self._conditions)
|
||
|
|
)
|
||
|
|
)
|
||
|
|
|
||
|
|
return self.__repr
|
||
|
|
|
||
|
|
def __str__(self):
|
||
|
|
def _condition_to_logic(feature, value):
|
||
|
|
"""
|
||
|
|
Return a compact, predicate-logic styled string representation
|
||
|
|
of the given condition.
|
||
|
|
"""
|
||
|
|
return '{0}:{1}@[{2}]'.format(
|
||
|
|
feature.PROPERTY_NAME,
|
||
|
|
value,
|
||
|
|
",".join(str(w) for w in feature.positions)
|
||
|
|
)
|
||
|
|
|
||
|
|
conditions = ' & '.join([_condition_to_logic(f, v) for (f, v) in self._conditions])
|
||
|
|
s = '{0}->{1} if {2}'.format(
|
||
|
|
self.original_tag,
|
||
|
|
self.replacement_tag,
|
||
|
|
conditions
|
||
|
|
)
|
||
|
|
|
||
|
|
return s
|
||
|
|
|
||
|
|
def format(self, fmt):
|
||
|
|
"""
|
||
|
|
Return a string representation of this rule.
|
||
|
|
|
||
|
|
>>> from nltk.tbl.rule import Rule
|
||
|
|
>>> from nltk.tag.brill import Pos
|
||
|
|
|
||
|
|
>>> r = Rule("23", "VB", "NN", [(Pos([-2,-1]), 'DT')])
|
||
|
|
|
||
|
|
r.format("str") == str(r)
|
||
|
|
True
|
||
|
|
>>> r.format("str")
|
||
|
|
'VB->NN if Pos:DT@[-2,-1]'
|
||
|
|
|
||
|
|
r.format("repr") == repr(r)
|
||
|
|
True
|
||
|
|
>>> r.format("repr")
|
||
|
|
"Rule('23', 'VB', 'NN', [(Pos([-2, -1]),'DT')])"
|
||
|
|
|
||
|
|
>>> r.format("verbose")
|
||
|
|
'VB -> NN if the Pos of words i-2...i-1 is "DT"'
|
||
|
|
|
||
|
|
>>> r.format("not_found")
|
||
|
|
Traceback (most recent call last):
|
||
|
|
File "<stdin>", line 1, in <module>
|
||
|
|
File "nltk/tbl/rule.py", line 256, in format
|
||
|
|
raise ValueError("unknown rule format spec: {0}".format(fmt))
|
||
|
|
ValueError: unknown rule format spec: not_found
|
||
|
|
>>>
|
||
|
|
|
||
|
|
:param fmt: format specification
|
||
|
|
:type fmt: str
|
||
|
|
:return: string representation
|
||
|
|
:rtype: str
|
||
|
|
"""
|
||
|
|
if fmt == "str":
|
||
|
|
return self.__str__()
|
||
|
|
elif fmt == "repr":
|
||
|
|
return self.__repr__()
|
||
|
|
elif fmt == "verbose":
|
||
|
|
return self._verbose_format()
|
||
|
|
else:
|
||
|
|
raise ValueError("unknown rule format spec: {0}".format(fmt))
|
||
|
|
|
||
|
|
def _verbose_format(self):
|
||
|
|
"""
|
||
|
|
Return a wordy, human-readable string representation
|
||
|
|
of the given rule.
|
||
|
|
|
||
|
|
Not sure how useful this is.
|
||
|
|
"""
|
||
|
|
def condition_to_str(feature, value):
|
||
|
|
return ('the %s of %s is "%s"' %
|
||
|
|
(feature.PROPERTY_NAME, range_to_str(feature.positions), value))
|
||
|
|
|
||
|
|
def range_to_str(positions):
|
||
|
|
if len(positions) == 1:
|
||
|
|
p = positions[0]
|
||
|
|
if p == 0:
|
||
|
|
return 'this word'
|
||
|
|
if p == -1:
|
||
|
|
return 'the preceding word'
|
||
|
|
elif p == 1:
|
||
|
|
return 'the following word'
|
||
|
|
elif p < 0:
|
||
|
|
return 'word i-%d' % -p
|
||
|
|
elif p > 0:
|
||
|
|
return 'word i+%d' % p
|
||
|
|
else:
|
||
|
|
# for complete compatibility with the wordy format of nltk2
|
||
|
|
mx = max(positions)
|
||
|
|
mn = min(positions)
|
||
|
|
if mx - mn == len(positions) - 1:
|
||
|
|
return 'words i%+d...i%+d' % (mn, mx)
|
||
|
|
else:
|
||
|
|
return 'words {%s}' % (",".join("i%+d" % d for d in positions),)
|
||
|
|
|
||
|
|
replacement = '%s -> %s' % (self.original_tag, self.replacement_tag)
|
||
|
|
conditions = (' if ' if self._conditions else "") + ', and '.join(
|
||
|
|
condition_to_str(f, v) for (f, v) in self._conditions
|
||
|
|
)
|
||
|
|
return replacement + conditions
|