Source code for nltk.misc.minimalset

# Natural Language Toolkit: Minimal Sets
# Copyright (C) 2001-2023 NLTK Project
# Author: Steven Bird <>
# URL: <>
# For license information, see LICENSE.TXT

from collections import defaultdict

[docs]class MinimalSet: """ 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'. """
[docs] 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)
[docs] 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
[docs] 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]
[docs] def display(self, context, target, default=""): if (context, target) in self._displays: return self._displays[(context, target)] else: return default
[docs] def display_all(self, context): result = [] for target in self._targets: x = self.display(context, target) if x: result.append(x) return result
[docs] def targets(self): return self._targets