Duee1.0信息提取句子级数据预处理

import os

import sys

import json

def read_by_lines(path):

result = list()

with open(path, "r", encoding="utf8") as infile:

for line in infile:

result.append(line.strip())

return result

def write_by_lines(path, data):

with open(path, "w", encoding="utf8") as outfile:

outfile.write(d + "\\n") for d in data

def data_process(path, model="trigger", is_predict=False):

def label_data(data, start, l, _type):

for i in range(start, start + l):#从起始索引到结束

suffix = "B-" if i == start else "I-" #前缀

datai = "{}{}".format(suffix, _type)

return data

sentences = \[\]

output = "text_a" if is_predict else "text_a\\tlabel"#文本,标签

with open(path) as f:

for line in f:

d_json = json.loads(line.strip())#每一行

_id = d_json"id"#id

text_a = [

"," if t == " " or t == "\n" or t == "\t" else t

for t in list(d_json"text".lower())

]# 文本

if is_predict:

sentences.append({"text": d_json"text", "id": _id})

output.append('\002'.join(text_a))

else:

if model == "trigger":

labels = "O" * len(text_a)#标签初始化为全部非实体

if len(d_json.get("event_list", \[\])) == 0:

continue

for event in d_json.get("event_list"):

event_type = event"event_type"#事件类型

start = event"trigger_start_index"#触发词起始索引

trigger = event"trigger"#触发池

#为触发词设置labels

labels = label_data(labels, start, len(trigger),

event_type)

output.append("{}\t{}".format('\002'.join(text_a),

'\002'.join(labels)))

elif model == "role":

labels = "O" * len(text_a)#标签

if len(d_json.get("event_list", \[\])) == 0:

continue

for event in d_json.get("event_list"):

for arg in event"arguments":

role_type = arg"role"#论元角色类型

argument = arg"argument"#论元

start = arg"argument_start_index"#论元起始

labels = label_data(labels, start, len(argument),

role_type)

output.append("{}\t{}".format('\002'.join(text_a),

'\002'.join(labels)))

return output

def schema_process(path, model="trigger"):

def label_add(labels, _type):

if "B-{}".format(_type) not in labels:#不在里面就添加

labels.extend("B-{}".format(_type), "I-{}".format(_type))#B-,I-

return labels

labels = \[\]#存放事件类型标签或角色标签

for line in read_by_lines(path):

d_json = json.loads(line.strip())

if model == "trigger":

labels = label_add(labels, d_json"event_type")

elif model == "role":

for role in d_json"role_list":

labels = label_add(labels, role"role")

labels.append("O")

tags = \[\]

for index, label in enumerate(labels):

tags.append("{}\t{}".format(index, label))

return tags

conf_dir = "./conf/DuEE1.0"

schema_path ='./datasets/DuEE_1_0/event_schema.json'

tags_trigger_path = "{}/trigger_tag.dict".format(conf_dir)

tags_role_path = "{}/role_tag.dict".format(conf_dir)

read_by_lines(schema_path)0

!unzip DuEE_1_0.zip -d ./datasets/

tags_trigger = schema_process(schema_path, "trigger")

os.makedirs(conf_dir,exist_ok=True)

write_by_lines(tags_trigger_path, tags_trigger)

tags_role = schema_process(schema_path, "role")

write_by_lines(tags_role_path, tags_role)

data_dir = "./datasets/DuEE1.0"

trigger_save_dir = "{}/trigger".format(data_dir)

role_save_dir = "{}/role".format(data_dir)

if not os.path.exists(trigger_save_dir):

os.makedirs(trigger_save_dir)

if not os.path.exists(role_save_dir):

os.makedirs(role_save_dir)

train_tri = data_process("./datasets/DuEE_1_0/train.json","trigger")

read_by_lines('./datasets/DuEE_1_0/train.json')0

write_by_lines("{}/train.tsv".format(trigger_save_dir), train_tri)

dev_tri = data_process("./datasets/DuEE_1_0/dev.json","trigger")

write_by_lines("{}/dev.tsv".format(trigger_save_dir), dev_tri)

test_tri = data_process("./datasets/DuEE_1_0/test.json", "trigger")

write_by_lines("{}/test.tsv".format(trigger_save_dir), test_tri)

train_role = data_process("./datasets/DuEE_1_0/train.json", "role")

write_by_lines("{}/train.tsv".format(role_save_dir), train_role)

dev_role = data_process("./datasets/DuEE_1_0/dev.json", "role")

write_by_lines("{}/dev.tsv".format(role_save_dir), dev_role)

test_role = data_process("./datasets/DuEE_1_0/test.json", "role")

write_by_lines("{}/test.tsv".format(role_save_dir), test_role)

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