def main(in_file='/data/SMP-CAIL2020-test1.csv',
out_file='/output/result1.csv'):
# importance = CheckImportance(cwd='gbtimportance')
# rank = CompRank(cwd='gbtrank')
courtresult = CompResult()
reason = CheckReason()
propose = CompPropose()
fact = CompFact()
opinion = CompOpinion()
#filter = CheckWordImportance()
with open(out_file, 'w', encoding='utf8') as fw:
with open(in_file, 'r', encoding="utf8") as f:
for line in f:
data = json.loads(line)
which_reason = ""
id = data.get('id')
text = data.get(
'text') # "text": [{"sentence":"001"},{"sentence":"002"}]
collected = []
#2.原告起诉
proposed = propose.getPropose(text)
#3.查明
facts = fact.getFact(text)
#4.法院意见
opinions = opinion.getOpinion(text)
# 5.6 依据+判决结果
trialresults = courtresult.getCourtResult(text)
#1. 纠纷原因
for i, sentence in enumerate(text):
if reason.isArgueReason(sentence["sentence"]):
which_reason = reason.isArgueReason(
sentence["sentence"])
break
data['reason'] = which_reason
dup = set()
for ll in (proposed, facts, opinions, trialresults):
for line in ll:
if line not in dup:
collected.append({'sentence': line})
dup.add(line)
data['text'] = collected
fw.write(json.dumps(data, ensure_ascii=False) + '\n')
class Segment_Abstract(object):
def __init__(self):
self.courtresult = CompResult()
self.reason = CheckReason()
self.propose = CompPropose()
self.fact = CompFact()
self.opinion = CompOpinion()
def get_abstract(self, data):
"""
:intput: document sentence list
:return: abstract sentence list
"""
which_reason = ""
id = data.get('id')
text = data.get('text') # "text": [{"sentence":"001"},{"sentence":"002"}]
collected = []
# 2.原告起诉
proposed = self.propose.getPropose(text)
# 3.查明
facts = self.fact.getFact(text)
# 4.法院意见
opinions = self.opinion.getOpinion(text)
# 5.6 依据+判决结果
trialresults = self.courtresult.getCourtResult(text)
# 1. 纠纷原因
for i, sentence in enumerate(text):
which_reason = self.reason.isArgueReason(sentence["sentence"])
if which_reason:
break
if i > 3:
break
if which_reason:
data['reason'] = which_reason
else:
data['reason'] = ''
dup = set()
for ll in (proposed, facts, opinions, trialresults):
for line in ll:
if line not in dup:
collected.append({'sentence': line})
dup.add(line)
data['text'] = collected
return data
# if re.search(r"诉讼请求：", sent_text):
# text0 = text[i]["sentence"]
# text1 = text[i + 1]["sentence"]
# text2 = text[i + 2]["sentence"]
# break
# else:
# text0 = text[11]["sentence"]
# text1 = text[12]["sentence"]
# text2 = text[13]["sentence"]
# result = text0 + text1 + text2
# return result
if __name__ == "__main__":
importance = CheckImportance(cwd='gbtimportance')
rank = CompRank(cwd='gbtrank')
courtresult = CompResult(cwd='gbtresult')
reason = CheckReason()
propose = CompPropose()
fact = CompFact()
opinion = CompOpinion()
with open(output_path, 'w', encoding='utf8') as fw:
with open(input_path, 'r', encoding="utf8") as f:
for line in f:
data = json.loads(line)
which_reason = ""
id = data.get('id')
text = data.get(
'text') # "text": [{"sentence":"001"},{"sentence":"002"}]
collected = []
def __init__(self):
self.courtresult = CompResult()
self.reason = CheckReason()
self.propose = CompPropose()
self.fact = CompFact()
self.opinion = CompOpinion()
def main(in_file='/data/SMP-CAIL2020-test1.csv',
out_file='/output/result1.csv'):
importance = CheckImportance(cwd='gbtimportance')
rank = CompRank(cwd='gbtrank')
courtresult = CompResult()
reason = CheckReason()
propose = CompPropose()
fact = CompFact()
opinion = CompOpinion()
filter = CheckWordImportance()
with open(out_file, 'w', encoding='utf8') as fw:
with open(in_file, 'r', encoding="utf8") as f:
for line in f:
data = json.loads(line)
which_reason = ""
id = data.get('id')
text = data.get(
'text') # "text": [{"sentence":"001"},{"sentence":"002"}]
collected = []
#2.原告起诉
proposed = propose.getPropose(text)
#3.查明
facts = fact.getFact(text)
#4.法院意见
opinions = opinion.getOpinion(text)
# 5.6 依据+判决结果
trialresults = courtresult.getCourtResult(text)
#1. 纠纷原因
for i, sentence in enumerate(text):
if reason.isArgueReason(sentence["sentence"]):
which_reason = reason.isArgueReason(
sentence["sentence"])
break
#####OUTPUT#######
#head
summary = []
# 1. 纠纷理由
if which_reason:
summary.append("原被告系%s纠纷关系。" % which_reason)
else:
summary.append(reason.checkArgueReason(text))
print(summary)
#body
# 2.原告诉称; 3.查明 4.本院认为 5.6.法律依据、判决结果
def filtertool(somelist):
newlist = [
line for line in somelist
if importance.checkImportance(line)
]
if len(newlist) == 0:
return somelist
return newlist
summary.extend(filtertool(proposed))
summary.extend(filtertool(facts))
summary.extend(filtertool(opinions))
summary.extend(trialresults)
if len(collected) < 1000:
pass
else:
# collected = [sent for sent in collected if len(sent) > 0]
sentrank = []
for sentence in collected:
sentrank.append(rank.checkRank(sentence))
rank2sent = dict()
for key, v in zip(sentrank, collected):
try:
rank2sent[key].append(v)
except KeyError:
rank2sent[key] = [v]
for key in sorted(rank2sent.keys()):
summary.extend(rank2sent[key])
# 过滤
# summary = [line for line in summary if importance.checkImportance(line)]
# summary = filter.checkWordImportance(summary)
summary = "".join(summary)
result = dict(id=id, summary=summary)
fw.write(json.dumps(result, ensure_ascii=False) + '\n')
def main(in_file='/data/SMP-CAIL2020-test1.csv',
out_file='/output/result1.csv'):
# importance = CheckImportance(cwd='gbtimportance')
# rank = CompRank(cwd='gbtrank')
courtresult = CompResult()
reason = CheckReason()
propose = CompPropose()
fact = CompFact()
opinion = CompOpinion()
# filter = CheckWordImportance()
with open(out_file, 'w', encoding='utf8') as fw:
with open(in_file, 'r', encoding="utf8") as f:
for line in f:
data = json.loads(line)
which_reason = ""
id = data.get('id')
text = data.get(
'text') # "text": [{"sentence":"001"},{"sentence":"002"}]
collected = []
#2.原告起诉
proposed = propose.getPropose(text)
#3.查明
facts = fact.getFact(text)
#4.法院意见
opinions = opinion.getOpinion(text)
# 5.6 依据+判决结果
trialresults = courtresult.getCourtResult(text)
#1. 纠纷原因
for i, sentence in enumerate(text):
which_reason = reason.isArgueReason(sentence["sentence"])
if which_reason:
break
if i > 3:
break
if which_reason:
data['reason'] = which_reason
else:
data['reason'] = ''
dup = set()
for ll in (proposed, facts, opinions, trialresults):
for line in ll:
if line not in dup:
collected.append({'sentence': line})
dup.add(line)
data['text'] = collected
#####OUTPUT#######
#head
# summary = []
# # 1. 纠纷理由
# if which_reason:
# summary.append("原被告系%s纠纷关系。" % which_reason)
# else:
# summary.append(reason.checkArgueReason(text))
# print(summary)
#
# #body
# # 2.原告诉称; 3.查明 4.本院认为 5.6.法律依据、判决结果
# def filtertool(somelist):
# newlist = [line for line in somelist if importance.checkImportance(line)]
# if len(newlist)==0:
# return somelist
# return newlist
#
# summary.extend(filtertool(proposed))
# summary.extend(filtertool(facts))
# summary.extend(filtertool(opinions))
# summary.extend(trialresults)
#
# if len(collected) < 1000:
# pass
# else:
# # collected = [sent for sent in collected if len(sent) > 0]
#
# sentrank = []
# for sentence in collected:
# sentrank.append(rank.checkRank(sentence))
# rank2sent = dict()
# for key, v in zip(sentrank, collected):
# try:
# rank2sent[key].append(v)
# except KeyError:
# rank2sent[key] = [v]
# for key in sorted(rank2sent.keys()):
# summary.extend(rank2sent[key])
#
# # 过滤
# # summary = [line for line in summary if importance.checkImportance(line)]
# # summary = filter.checkWordImportance(summary)
# summary = "".join(summary)
# result = dict(
# id=id,
# summary=summary
# )
fw.write(json.dumps(data, ensure_ascii=False) + '\n')
# if re.search(r"诉讼请求：", sent_text):
# text0 = text[i]["sentence"]
# text1 = text[i + 1]["sentence"]
# text2 = text[i + 2]["sentence"]
# break
# else:
# text0 = text[11]["sentence"]
# text1 = text[12]["sentence"]
# text2 = text[13]["sentence"]
# result = text0 + text1 + text2
# return result
if __name__ == "__main__":
importance = CheckImportance(cwd='gbtimportance')
rank = CompRank(cwd='gbtrank')
courtresult = CompResult()
reason = CheckReason()
propose = CompPropose()
fact = CompFact()
opinion = CompOpinion()
filter = CheckWordImportance()
with open(output_path, 'w', encoding='utf8') as fw:
with open(input_path, 'r', encoding="utf8") as f:
for line in f:
data = json.loads(line)
which_reason = ""
id = data.get('id')
text = data.get(
'text') # "text": [{"sentence":"001"},{"sentence":"002"}]
collected = []