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from __future__ import print_function
from __future__ import unicode_literals
from builtins import str, bytes, dict, int
import os
import sys
sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", ".."))
from pattern.en import wordnet
from pattern.en import NOUN, VERB
# WordNet is a lexical database for the English language.
# It groups English words into sets of synonyms called synsets, provides short, general definitions,
# and records the various semantic relations between these synonym sets.
# For a given word, WordNet yields a list of synsets that
# represent different "senses" in which the word can be understood.
for synset in wordnet.synsets("train", pos=NOUN):
print("Description: %s" % synset.gloss) # Definition string.
print(" Synonyms: %s" % synset.senses) # List of synonyms in this sense.
print(" Hypernym: %s" % synset.hypernym) # Synset one step higher in the semantic network.
print(" Hyponyms: %s" % synset.hyponyms()) # List of synsets that are more specific.
print(" Holonyms: %s" % synset.holonyms()) # List of synsets of which this synset is part/member.
print(" Meronyms: %s" % synset.meronyms()) # List of synsets that are part/member of this synset.
print("")
# What is the common ancestor (hypernym) of "cat" and "dog"?
a = wordnet.synsets("cat")[0]
b = wordnet.synsets("dog")[0]
print("Common ancestor: %s" % wordnet.ancestor(a, b))
print("")
# Synset.hypernyms(recursive=True) returns all parents of the synset,
# Synset.hyponyms(recursive=True) returns all children,
# optionally up to a given depth.
# What kind of animal nouns are also verbs?
synset = wordnet.synsets("animal")[0]
for s in synset.hyponyms(recursive=True, depth=2):
for word in s.senses:
if word in wordnet.VERBS():
print("%s => %s" % (word, wordnet.synsets(word, pos=VERB)))
# Synset.similarity() returns an estimate of the semantic similarity to another synset,
# based on Lin's semantic distance measure and Resnik Information Content.
# Lower values indicate higher similarity.
a = wordnet.synsets("cat")[0] # river, bicycle
s = []
for word in ["poodle", "cat", "boat", "carrot", "rocket",
"spaghetti", "idea", "grass", "education",
"lake", "school", "balloon", "lion"]:
b = wordnet.synsets(word)[0]
s.append((a.similarity(b), word))
print("")
print("Similarity to %s: %s" % (a.senses[0], sorted(s)))
print("")
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