from k54 import load_xml
import re
# sentence_list[sentenceIndex][tokenIndex]で任意の単語が取得できるようなリストを作成
sentence_list = [[]] # インデックス調整の為予め1つ要素を入れておく
for sentence in load_xml()['root']['document']['sentences']['sentence']:
token_list = [''] # インデックス調整の為（ｒｙ
# 13文目の為の処理
if isinstance(sentence['tokens']['token'], dict):
token_list.append(sentence['tokens']['token']['word'])
else:
for token in sentence['tokens']['token']:
token_list.append(token['word'])
sentence_list.append(token_list)
for core in load_xml()['root']['document']['coreference']['coreference']:
rep = ''
for mention in core['mention']:
if '@representative' in mention: # 代表参照表現なら文字列を取得
rep = (mention['text'])
else:
sent = int(mention['sentence'])
start = int(mention['start'])
end = int(mention['end'])
# 参照表現の先頭に '「 [代表表現] ( ' を追加
sentence_list[sent][
start] = '「 ' + rep + ' ( ' + sentence_list[sent][start]
from k54 import load_xml
def print_person_name(word='', pos='', ner=''):
if pos == 'NNP' and ner == 'PERSON':
print(word)
for sentence in load_xml()['root']['document']['sentences']['sentence']:
tokens = sentence['tokens']['token']
# tokenが1つしか無い時の処理
if isinstance(tokens, dict):
print_person_name(tokens['word'], tokens['POS'], tokens['NER'])
continue
for t in tokens:
print_person_name(t['word'], t['POS'], t['NER'])
from k54 import load_xml
import re
parse_strings = [sentences['parse'] for sentences in load_xml()['root']['document']['sentences']['sentence']]
for ps in parse_strings:
start = 0 # (NP の開始位置を保存
while len(ps) > start:
start += 1
if ps[start:start + 3] == '(NP': # (NPが見つかった時
# 終端位置endを探す、countは()の数をカウント
end, count = start + 1, 1
while count: # count が0以上の間
if ps[end] == '(':
count += 1
elif ps[end] == ')':
count -= 1
end += 1
outList = []
# 先頭と終端がわかったので、中に入っている単語だけ抜き取る
for word in ps[start:end + 1].split(' '):
if word and word[-1] == ')':
outList.append(word.replace(')', ''))
outStr = re.sub(r' ([,.;:?!])', r'\1', ' '.join(outList)) # カンマやピリオドの前の空白を削除
outStr = outStr.replace('-LRB- ', '(').replace(' -RRB-', ')') # ()を復元
print(outStr)