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formatting

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This commit is contained in:
svlandeg 2019-07-19 14:52:45 +02:00
parent 41fb5204ba
commit f75d1299a7
1 changed files with 12 additions and 9 deletions
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21
bin/wiki_entity_linking/training_set_creator.py
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@ -365,9 +365,8 @@ def read_training(nlp, training_dir, dev, limit, kb=None):
encoding="utf8", encoding="utf8",
) as f: ) as f:
text = f.read() text = f.read()
if ( # threshold for convenience / speed of processing
len(text) < 30000 if len(text) < 30000:
): # threshold for convenience / speed of processing
current_doc = nlp(text) current_doc = nlp(text)
current_article_id = article_id current_article_id = article_id
ents_by_offset = dict() ents_by_offset = dict()
@ -386,7 +385,6 @@ def read_training(nlp, training_dir, dev, limit, kb=None):
except Exception as e: except Exception as e:
print("Problem parsing article", article_id, e) print("Problem parsing article", article_id, e)
skip_articles.add(article_id) skip_articles.add(article_id)
raise e
# repeat checking this condition in case an exception was thrown # repeat checking this condition in case an exception was thrown
if current_doc and (current_article_id == article_id): if current_doc and (current_article_id == article_id):
@ -404,13 +402,17 @@ def read_training(nlp, training_dir, dev, limit, kb=None):
gold_entities = {} gold_entities = {}
found_useful = False found_useful = False
for ent in sent.ents: for ent in sent.ents:
if ent.start_char == gold_start and ent.end_char == gold_end: entry = (ent.start_char, ent.end_char)
gold_entry = (gold_start, gold_end)
if entry == gold_entry:
# add both pos and neg examples (in random order) # add both pos and neg examples (in random order)
# this will exclude examples not in the KB # this will exclude examples not in the KB
if kb: if kb:
value_by_id = {} value_by_id = {}
candidates = kb.get_candidates(alias) candidates = kb.get_candidates(alias)
candidate_ids = [c.entity_ for c in candidates] candidate_ids = [
c.entity_ for c in candidates
]
random.shuffle(candidate_ids) random.shuffle(candidate_ids)
for kb_id in candidate_ids: for kb_id in candidate_ids:
found_useful = True found_useful = True
@ -418,16 +420,17 @@ def read_training(nlp, training_dir, dev, limit, kb=None):
value_by_id[kb_id] = 0.0 value_by_id[kb_id] = 0.0
else: else:
value_by_id[kb_id] = 1.0 value_by_id[kb_id] = 1.0
gold_entities[(ent.start_char, ent.end_char)] = value_by_id gold_entities[entry] = value_by_id
# if no KB, keep all positive examples # if no KB, keep all positive examples
else: else:
found_useful = True found_useful = True
value_by_id = {wd_id: 1.0} value_by_id = {wd_id: 1.0}
gold_entities[(ent.start_char, ent.end_char)] = value_by_id
gold_entities[entry] = value_by_id
# currently feeding the gold data one entity per sentence at a time # currently feeding the gold data one entity per sentence at a time
# setting all other entities to empty gold dictionary # setting all other entities to empty gold dictionary
else: else:
gold_entities[(ent.start_char, ent.end_char)] = {} gold_entities[entry] = {}
if found_useful: if found_useful:
gold = GoldParse(doc=sent, links=gold_entities) gold = GoldParse(doc=sent, links=gold_entities)
data.append((sent, gold)) data.append((sent, gold))