83 lines
2.8 KiB
Python
83 lines
2.8 KiB
Python
# Natural Language Toolkit: Minimal Sets
|
|
#
|
|
# Copyright (C) 2001-2018 NLTK Project
|
|
# Author: Steven Bird <stevenbird1@gmail.com>
|
|
# URL: <http://nltk.org>
|
|
# For license information, see LICENSE.TXT
|
|
|
|
from collections import defaultdict
|
|
|
|
class MinimalSet(object):
|
|
"""
|
|
Find contexts where more than one possible target value can
|
|
appear. E.g. if targets are word-initial letters, and contexts
|
|
are the remainders of words, then we would like to find cases like
|
|
"fat" vs "cat", and "training" vs "draining". If targets are
|
|
parts-of-speech and contexts are words, then we would like to find
|
|
cases like wind (noun) 'air in rapid motion', vs wind (verb)
|
|
'coil, wrap'.
|
|
"""
|
|
def __init__(self, parameters=None):
|
|
"""
|
|
Create a new minimal set.
|
|
|
|
:param parameters: The (context, target, display) tuples for the item
|
|
:type parameters: list(tuple(str, str, str))
|
|
"""
|
|
self._targets = set() # the contrastive information
|
|
self._contexts = set() # what we are controlling for
|
|
self._seen = defaultdict(set) # to record what we have seen
|
|
self._displays = {} # what we will display
|
|
|
|
if parameters:
|
|
for context, target, display in parameters:
|
|
self.add(context, target, display)
|
|
|
|
def add(self, context, target, display):
|
|
"""
|
|
Add a new item to the minimal set, having the specified
|
|
context, target, and display form.
|
|
|
|
:param context: The context in which the item of interest appears
|
|
:type context: str
|
|
:param target: The item of interest
|
|
:type target: str
|
|
:param display: The information to be reported for each item
|
|
:type display: str
|
|
"""
|
|
# Store the set of targets that occurred in this context
|
|
self._seen[context].add(target)
|
|
|
|
# Keep track of which contexts and targets we have seen
|
|
self._contexts.add(context)
|
|
self._targets.add(target)
|
|
|
|
# For a given context and target, store the display form
|
|
self._displays[(context, target)] = display
|
|
|
|
def contexts(self, minimum=2):
|
|
"""
|
|
Determine which contexts occurred with enough distinct targets.
|
|
|
|
:param minimum: the minimum number of distinct target forms
|
|
:type minimum: int
|
|
:rtype list
|
|
"""
|
|
return [c for c in self._contexts if len(self._seen[c]) >= minimum]
|
|
|
|
def display(self, context, target, default=""):
|
|
if (context, target) in self._displays:
|
|
return self._displays[(context, target)]
|
|
else:
|
|
return default
|
|
|
|
def display_all(self, context):
|
|
result = []
|
|
for target in self._targets:
|
|
x = self.display(context, target)
|
|
if x: result.append(x)
|
|
return result
|
|
|
|
def targets(self):
|
|
return self._targets
|
|
|