mirror of
https://github.com/explosion/spaCy.git
synced 2024-11-15 14:17:58 +03:00
116 lines
4.0 KiB
Python
116 lines
4.0 KiB
Python
"""
|
|
Get a mapping of (lemma, sense_number)-->supersense, and a mapping
|
|
(lemma, ON group)-->(lemma, sense_number).
|
|
|
|
Then we can read the OntoNotes token-->(lemma, ON group) annotations, and resolve
|
|
them to the token-->supersense annotations we want to train from.
|
|
|
|
supersense: A WordNet lexical file number
|
|
sense_number: A WordNet sense key, found in e.g. wordnet/index.sense file
|
|
lex_filenum: A WordNet "super sense", or lexical file number.
|
|
onto_group: An OntoNotes sense grouping, which dominates zero or more WN senses.
|
|
"""
|
|
from __future__ import division
|
|
|
|
from os import path
|
|
import os
|
|
import re
|
|
import codecs
|
|
|
|
|
|
def get_sense_to_ssense(index_dot_sense_loc):
|
|
mapping = {}
|
|
pos_tags = [None, 'n', 'v', 'j', 'a', 's']
|
|
for line in codecs.open(index_dot_sense_loc, 'r', 'utf8'):
|
|
sense_key, synset_offset, sense_number, tag_cnt = line.split()
|
|
lemma, lex_sense = sense_key.split('%')
|
|
ss_type, lex_filenum, lex_id, head_word, head_id = lex_sense.split(':')
|
|
pos = pos_tags[int(ss_type)]
|
|
mapping[(lemma, pos, int(sense_number))] = int(lex_filenum)
|
|
return mapping
|
|
|
|
|
|
sense_group_re = re.compile(r'<sense .*?</sense>', re.DOTALL)
|
|
wn_mapping_re = re.compile(r'version="3.0">([^<]+)<')
|
|
def get_og_to_sense(sense_inv_dir):
|
|
mapping = {}
|
|
for filename in os.listdir(sense_inv_dir):
|
|
if not filename.endswith('.xml'):
|
|
continue
|
|
if '-' not in filename:
|
|
continue
|
|
lemma, pos = filename.split('-')[:2]
|
|
pos = pos[0]
|
|
# Word is these often don't validate, because of course. So, just parse
|
|
# with regex...
|
|
xml_str = open(path.join(sense_inv_dir, filename)).read()
|
|
for sense_grouping in sense_group_re.findall(xml_str):
|
|
group_num = sense_grouping.split('n="')[1].split('"')[0]
|
|
if not group_num:
|
|
continue
|
|
|
|
group_num = int(float(group_num))
|
|
key = (lemma, pos, int(group_num))
|
|
mapping.setdefault(key, [])
|
|
wn_elem = wn_mapping_re.search(sense_grouping)
|
|
if wn_elem is not None:
|
|
sense_num_str = wn_elem.groups()[0].replace('.', ',')
|
|
sense_ids = [(lemma, pos, int(n)) for n in sense_num_str.strip().split(',')]
|
|
mapping[key].extend(sense_ids)
|
|
return mapping
|
|
|
|
|
|
def get_lexnames(loc):
|
|
names = {}
|
|
for line in open(loc):
|
|
id_, name, syn_type = line.split()
|
|
names[int(id_)] = name
|
|
return names
|
|
|
|
|
|
def get_og_to_ssenses(wordnet_dir, onto_dir):
|
|
sense_inv_dir = path.join(onto_dir, 'data', 'english', 'metadata', 'sense-inventories')
|
|
og_to_sense = get_og_to_sense(sense_inv_dir)
|
|
sense_to_ssense = get_sense_to_ssense(path.join(wordnet_dir, 'index.sense'))
|
|
lexnames = get_lexnames(path.join(wordnet_dir, 'lexnames'))
|
|
|
|
mapping = {}
|
|
for key, senses in og_to_sense.items():
|
|
if senses is not None:
|
|
mapping[key] = set([lexnames[sense_to_ssense[s_key]]
|
|
for s_key in senses if s_key in sense_to_ssense])
|
|
return mapping
|
|
|
|
|
|
def make_supersense_dict(wordnet_dir):
|
|
sense_to_ssense = get_sense_to_ssense(path.join(wordnet_dir, 'index.sense'))
|
|
gather = {}
|
|
for (word, pos, sense), supersense in sense_to_ssense.items():
|
|
key = (word, pos)
|
|
gather.setdefault((word, pos), []).append((int(sense), supersense))
|
|
mapping = {}
|
|
for (word, pos), senses in gather.items():
|
|
n_senses = len(senses)
|
|
probs = {}
|
|
remaining = 1.0
|
|
for sense, supersense in sorted(senses):
|
|
remaining /= 2
|
|
probs[supersense] = probs.get(supersense, 0.0) + remaining
|
|
for sense, supersense in sorted(senses):
|
|
probs[supersense] += remaining / len(senses)
|
|
mapping.setdefault(word, {}).update(probs)
|
|
return mapping
|
|
|
|
|
|
def main(wordnet_dir, onto_dir):
|
|
mapping = make_supersense_dict(wordnet_dir)
|
|
print mapping[('dog', 'v')]
|
|
print mapping[('dog', 'n')]
|
|
print mapping[('abandon', 'v')]
|
|
print mapping[('abandon', 'n')]
|
|
|
|
|
|
if __name__ == '__main__':
|
|
import plac
|
|
plac.call(main)
|