Python nltk.corpus.wordnet.all_synsets() Examples
The following are 4
code examples of nltk.corpus.wordnet.all_synsets().
You can vote up the ones you like or vote down the ones you don't like,
and go to the original project or source file by following the links above each example.
You may also want to check out all available functions/classes of the module
nltk.corpus.wordnet
, or try the search function
.
Example #1
Source File: definition_preprocessor.py From EWISE with Apache License 2.0 | 6 votes |
def process_definitions(self): self.definition_map = {} self.lemmakey_to_synset = {} n_empty_definitions = 0 print ("Processing definitions") all_synsets = wn.all_synsets() for s in tqdm(all_synsets): definition = s.definition().strip() if len(definition) == 0: n_empty_definitions = n_empty_definitions + 1 self.definition_map[s.name()] = definition lemmas = s.lemmas() for lemma in lemmas: key = lemma.key() self.lemmakey_to_synset[key] = s.name() print ("#Empty definitions {}/{}".format(n_empty_definitions, len(self.definition_map))) synsets = sorted(self.definition_map.keys()) #self.synset_to_idx = {v:i for i,v in enumerate(self.synset_to_definition.keys())} self.synset_to_idx = {v:i for i,v in enumerate(synsets)} self.idx_to_synset = {v:i for i,v in self.synset_to_idx.items()} self.definitions = [self.definition_map[k] for k in synsets]
Example #2
Source File: extractors.py From PPP-QuestionParsing-Grammatical with GNU Affero General Public License v3.0 | 5 votes |
def buildNouns(): """ Returns the set of all nouns of NLTK """ return {x.name().split('.', 1)[0] for x in wn.all_synsets('n')}
Example #3
Source File: extractors.py From PPP-QuestionParsing-Grammatical with GNU Affero General Public License v3.0 | 5 votes |
def buildVerbs(): """ Returns the set of all verbs of NLTK """ return {x.name().split(".", 1)[0] for x in wn.all_synsets("v")}
Example #4
Source File: extract_wordnet.py From kb with Apache License 2.0 | 4 votes |
def extract_wordnet_from_nltk(entity_output_file, relation_output_file): from nltk.corpus import wordnet as wn import json # each node is a synset or synset+lemma # synsets have POS # synsets have several lemmas associated with them # each lemma is keyed by something like able%3:00:00:: # where string = lemma, first number is POS, then sense id # # in addition to the synset-synset and lemma-lemma relationships, # we will also add synset_lemma relationship for lemmas contained # in each synset with open(entity_output_file, 'w') as fent, \ open(relation_output_file, 'w') as frel: for synset in wn.all_synsets(): node = { 'id': synset.name(), 'pos': synset.pos(), 'lemmas': [lem.key() for lem in synset.lemmas()], 'examples': synset.examples(), 'definition': synset.definition(), 'type': 'synset', } fent.write(json.dumps(node) + '\n') # synset-synset relationships for relation in SYNSET_RELATIONSHIP_TYPES: entity2 = [rel_synset.name() for rel_synset in getattr(synset, relation)()] for e2 in entity2: frel.write('{}\t{}\t{}\n'.format(synset.name(), 'synset_' + relation, e2)) # now get synset-lemma and lemma-lemma relationships for lemma in synset.lemmas(): node = { 'id': lemma.key(), 'pos': synset.pos(), 'synset': synset.name(), 'type': 'lemma', 'count': lemma.count(), } fent.write(json.dumps(node) + '\n') frel.write('{}\t{}\t{}\n'.format(synset.name(), 'synset_lemma', lemma.key())) # lemma-lemma for relation in LEMMA_RELATIONSHIP_TYPES: entity2 = [rel_lemma.key() for rel_lemma in getattr(lemma, relation)()] for e2 in entity2: frel.write('{}\t{}\t{}\n'.format(synset.name(), 'lemma_' + relation, e2))