spaCy/bin/prepare_treebank.py

195 lines
6.1 KiB
Python

"""Convert OntoNotes into a json format.
doc: {
id: string,
paragraphs: [{
raw: string,
sents: [int],
tokens: [{
start: int,
tag: string,
head: int,
dep: string}],
ner: [{
start: int,
end: int,
label: string}],
brackets: [{
start: int,
end: int,
label: string}]}]}
Consumes output of spacy/munge/align_raw.py
"""
from __future__ import unicode_literals
import plac
import json
from os import path
import os
import re
import io
from collections import defaultdict
from spacy.munge import read_ptb
from spacy.munge import read_conll
from spacy.munge import read_ner
def _iter_raw_files(raw_loc):
files = json.load(open(raw_loc))
for f in files:
yield f
def format_doc(file_id, raw_paras, ptb_text, dep_text, ner_text):
ptb_sents = read_ptb.split(ptb_text)
dep_sents = read_conll.split(dep_text)
if len(ptb_sents) != len(dep_sents):
return None
if ner_text is not None:
ner_sents = read_ner.split(ner_text)
else:
ner_sents = [None] * len(ptb_sents)
i = 0
doc = {'id': file_id}
if raw_paras is None:
doc['paragraphs'] = [format_para(None, ptb_sents, dep_sents, ner_sents)]
#for ptb_sent, dep_sent, ner_sent in zip(ptb_sents, dep_sents, ner_sents):
# doc['paragraphs'].append(format_para(None, [ptb_sent], [dep_sent], [ner_sent]))
else:
doc['paragraphs'] = []
for raw_sents in raw_paras:
para = format_para(
' '.join(raw_sents).replace('<SEP>', ''),
ptb_sents[i:i+len(raw_sents)],
dep_sents[i:i+len(raw_sents)],
ner_sents[i:i+len(raw_sents)])
if para['sentences']:
doc['paragraphs'].append(para)
i += len(raw_sents)
return doc
def format_para(raw_text, ptb_sents, dep_sents, ner_sents):
para = {'raw': raw_text, 'sentences': []}
offset = 0
assert len(ptb_sents) == len(dep_sents) == len(ner_sents)
for ptb_text, dep_text, ner_text in zip(ptb_sents, dep_sents, ner_sents):
_, deps = read_conll.parse(dep_text, strip_bad_periods=True)
if deps and 'VERB' in [t['tag'] for t in deps]:
continue
if ner_text is not None:
_, ner = read_ner.parse(ner_text, strip_bad_periods=True)
else:
ner = ['-' for _ in deps]
_, brackets = read_ptb.parse(ptb_text, strip_bad_periods=True)
# Necessary because the ClearNLP converter deletes EDITED words.
if len(ner) != len(deps):
ner = ['-' for _ in deps]
para['sentences'].append(format_sentence(deps, ner, brackets))
return para
def format_sentence(deps, ner, brackets):
sent = {'tokens': [], 'brackets': []}
for token_id, (token, token_ent) in enumerate(zip(deps, ner)):
sent['tokens'].append(format_token(token_id, token, token_ent))
for label, start, end in brackets:
if start != end:
sent['brackets'].append({
'label': label,
'first': start,
'last': (end-1)})
return sent
def format_token(token_id, token, ner):
assert token_id == token['id']
head = (token['head'] - token_id) if token['head'] != -1 else 0
return {
'id': token_id,
'orth': token['word'],
'tag': token['tag'],
'head': head,
'dep': token['dep'],
'ner': ner}
def read_file(*pieces):
loc = path.join(*pieces)
if not path.exists(loc):
return None
else:
return io.open(loc, 'r', encoding='utf8').read().strip()
def get_file_names(section_dir, subsection):
filenames = []
for fn in os.listdir(path.join(section_dir, subsection)):
filenames.append(fn.rsplit('.', 1)[0])
return list(sorted(set(filenames)))
def read_wsj_with_source(onto_dir, raw_dir):
# Now do WSJ, with source alignment
onto_dir = path.join(onto_dir, 'data', 'english', 'annotations', 'nw', 'wsj')
docs = {}
for i in range(25):
section = str(i) if i >= 10 else ('0' + str(i))
raw_loc = path.join(raw_dir, 'wsj%s.json' % section)
for j, (filename, raw_paras) in enumerate(_iter_raw_files(raw_loc)):
if section == '00':
j += 1
if section == '04' and filename == '55':
continue
ptb = read_file(onto_dir, section, '%s.parse' % filename)
dep = read_file(onto_dir, section, '%s.parse.dep' % filename)
ner = read_file(onto_dir, section, '%s.name' % filename)
if ptb is not None and dep is not None:
docs[filename] = format_doc(filename, raw_paras, ptb, dep, ner)
return docs
def get_doc(onto_dir, file_path, wsj_docs):
filename = file_path.rsplit('/', 1)[1]
if filename in wsj_docs:
return wsj_docs[filename]
else:
ptb = read_file(onto_dir, file_path + '.parse')
dep = read_file(onto_dir, file_path + '.parse.dep')
ner = read_file(onto_dir, file_path + '.name')
if ptb is not None and dep is not None:
return format_doc(filename, None, ptb, dep, ner)
else:
return None
def read_ids(loc):
return open(loc).read().strip().split('\n')
def main(onto_dir, raw_dir, out_dir):
wsj_docs = read_wsj_with_source(onto_dir, raw_dir)
for partition in ('train', 'test', 'development'):
ids = read_ids(path.join(onto_dir, '%s.id' % partition))
docs_by_genre = defaultdict(list)
for file_path in ids:
doc = get_doc(onto_dir, file_path, wsj_docs)
if doc is not None:
genre = file_path.split('/')[3]
docs_by_genre[genre].append(doc)
part_dir = path.join(out_dir, partition)
if not path.exists(part_dir):
os.mkdir(part_dir)
for genre, docs in sorted(docs_by_genre.items()):
out_loc = path.join(part_dir, genre + '.json')
with open(out_loc, 'w') as file_:
json.dump(docs, file_, indent=4)
if __name__ == '__main__':
plac.call(main)