def gen_wn_lemmas(pos):
"""Generates POS-tag, synset ID, lemma.
That is all the info that we currently want from WordNet.
"""
for synset in wn.all_synsets(pos=POS_TO_WN.get(pos)):
for lemma in synset.lemmas():
yield pos, synset.name, lemma.name
def gen_wn_lemmas(pos=wn.NOUN):
"""Generates POS-tag, synset ID, lemma.
That is all the info that we currently want from WordNet.
TODO: get ILI links too to be able to make bilingual lexicons.
"""
for synset in wn.all_synsets(pos=pos):
for lemma in synset.lemmas():
yield pos, synset.name, lemma.name
if is_tag_allowed(
word_analysis
) and word not in basic and word not in foreign_words and has_relations(
synsets):
foreign_words[word] = None
print("Koostan töödeldud võõrsõnade loendit")
with open("foreign_processed.txt", "w", encoding="UTF-8") as file:
for word in foreign_words:
if len(word.split(" ")) <= 1:
if foreign_words[word] is None:
file.write(word + "\n")
else:
file.write(word + " " + foreign_words[word] + "\n")
foreign_words.clear()
print("Võõrsõnade loend töödeldud")
if __name__ == '__main__':
# Hoiatus!
# Kogu töötlemine võib võtta paar tundi.
print("Laadin kõik sünohulgad mällu...")
wn.all_synsets()
print("Laaditud")
process_frequency_list()
process_basic_list()
process_foreign_list()
import sys, os
_MY_DIR = os.path.dirname(__file__)
sys.path.insert(1,os.path.join(_MY_DIR,'..','..'))
from estnltk.wordnet import wn
FILE_ = os.path.join(_MY_DIR,'..','max_tax_depths.cnf')
max_depths = {}
for pos in 'bavn':
all_synsets = wn.all_synsets(pos)
n = len(all_synsets)
max_depth = -1
for i in range(n):
depth = all_synsets[i]._min_depth()
max_depth = depth if depth > max_depth else max_depth
max_depths[pos] = max_depth
with open(FILE_,'w') as fout:
for pos in max_depths:
fout.write("%s:%d\n"%(pos,max_depths[pos]))
from estnltk.wordnet import wn
from pprint import pprint
print(len(wn.all_synsets()))
pprint(wn.synsets("koer", pos=wn.VERB))
pprint(wn.synsets('koer'))
synset = wn.synset("king.n.01")
pprint(synset.name)
pprint(synset.pos)
pprint(synset.definition())
pprint(synset.examples())
pprint(synset.hypernyms())
pprint(synset.hyponyms())
pprint(synset.meronyms())
pprint(synset.holonyms())
pprint(synset.get_related_synsets('fuzzynym'))
target_synset = wn.synset('kinnas.n.01')
pprint(synset.path_similarity(target_synset))
pprint(synset.lch_similarity(target_synset))
pprint(synset.wup_similarity(target_synset))
pprint(synset.lowest_common_hypernyms(target_synset))
from estnltk.wordnet import wn
from pprint import pprint
print (len(wn.all_synsets()))
pprint(wn.synsets("koer",pos=wn.VERB))
pprint(wn.synsets('koer'))
synset = wn.synset("king.n.01")
pprint(synset.name)
pprint(synset.pos)
pprint(synset.definition())
pprint(synset.examples())
pprint(synset.hypernyms())
pprint(synset.hyponyms())
pprint(synset.meronyms())
pprint(synset.holonyms())
pprint(synset.get_related_synsets('fuzzynym'))
target_synset = wn.synset('kinnas.n.01')
pprint(synset.path_similarity(target_synset))
pprint(synset.lch_similarity(target_synset))
pprint(synset.wup_similarity(target_synset))
pprint(synset.lowest_common_hypernyms(target_synset))
