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An open-source and powerful Information Extraction toolkit based on GPT (GPT for Information Extraction; GPT4IE for short)。Note: we set a default openai key in the tool, you can tell us if the key reach the limit.

Home Page: http://124.221.16.143:8080/

License: MIT License

HTML 6.92% CSS 15.65% JavaScript 77.43%
event-extraction gpt-3 information-extraction ner prompt-toolkit relation-extraction

gpt4ie's Introduction

GPT4IE

we also provide a IE tool based on ChatGPT, you can see in ChatIE

Description

Note: we set a default openai key in the tool, you can tell us if the key reach the limit.

GPT4IE (GPT for Information Extraction) is a open-source and powerful IE tool demo. Enhanced by GPT3.5 and prompting, it aims to automatically extract structured information from a raw sentence and make a valuable in-depth analysis of the input sentence. Harnessing valuable structured information helps corporations make incisive and business–improving decisions.

We support the following functions:

Task Name Lauguages
RE entity-relation joint extraction Chinese, English
NER named entity recoginzation Chinese, English
EE event extraction Chinese, English

RE

This task aims to extract triples from plain texts, such as (China, capital, Beijing) , (《如懿传》, 主演, 周迅).

Input

  • sentence: a plain text.
  • relation type list (rtl)* : ['relation type 1', 'relation type 2', ...]
  • subject type list (stl)* : ['subject type 1', 'subject type 2', ...]
  • object type list (otl)* : ['object type 1', 'object type 2', ...]

PS: * denote optional, we set default value for them. But for better extraction, you should specify the three list according to application scenarios.

Examples

sentence: Bob worked for Google in Beijing, the capital of China.
rtl: ['location-located_in', 'administrative_division-country', 'person-place_lived', 'person-company', 'person-nationality', 'company-founders', 'country-administrative_divisions', 'person-children', 'country-capital', 'deceased_person-place_of_death', 'neighborhood-neighborhood_of', 'person-place_of_birth']
stl: ['organization', 'person', 'location', 'country']
otl: ['person', 'location', 'country', 'organization', 'city']
ouptut:
ouptut

sentence: 第五部:《如懿传》《如懿传》是一部古装宫廷情感电视剧,由汪俊执导,周迅、霍建华、张钧甯、董洁、辛芷蕾、童瑶、李纯、邬君梅等主演。
rtl: ['所属专辑', '成立日期', '海拔', '官方语言', '占地面积', '父亲', '歌手', '制片人', '导演', '首都', '主演', '董事长', '祖籍', '妻子', '母亲', '气候', '面积', '主角', '邮政编码', '简称', '出品公司', '注册资本', '编剧', '创始人', '毕业院校', '国籍', '专业代码', '朝代', '作者', '作词', '所在城市', '嘉宾', '总部地点', '人口数量', '代言人', '改编自', '校长', '丈夫', '主持人', '主题曲', '修业年限', '作曲', '号', '上映时间', '票房', '饰演', '配音', '获奖'] stl: ['国家', '行政区', '文学作品', '人物', '影视作品', '学校', '图书作品', '地点', '历史人物', '景点', '歌曲', '学科专业', '企业', '电视综艺', '机构', '企业/品牌', '娱乐人物']
otl: ['国家', '人物', 'Text', 'Date', '地点', '气候', '城市', '歌曲', '企业', 'Number', '音乐专辑', '学校', '作品', '语言']
ouptut:
ouptut


NER

This task aims to extract entities from plain texts, such as (LOC, Beijing) , (人物, 周恩来).

Input

  • sentence: a plain text.
  • entity type list (etl)* : ['entity type 1', 'entity type 2', ...]

PS: * denote optional, we set default value for it. But for better extraction, you should specify the list according to application scenarios.

Examples

sentence: Bob worked for Google in Beijing, the capital of China.
etl: ['LOC', 'MISC', 'ORG', 'PER']
ouptut:
ouptut

sentence: 在过去的五年中,致公党在***理论指引下,遵循社会主义初级阶段的基本路线,努力实践致公党十大提出的发挥参政党职能、加强自身建设的基本任务。
etl: ['组织机构', '地点', '人物']
ouptut:
ouptut


EE

This task aims to extract event from plain texts, such as {Life-Divorce: {Person: Bob, Time: today, Place: America}} , {竞赛行为-晋级: {时间: 无, 晋级方: 西北狼, 晋级赛事: 中甲榜首之争}}.

Input

  • sentence: a plain text.
  • event type list (etl)* : {'event type 1': ['argument role 1', 'argument role 2', ...], ...}

PS: * denote optional, we set default value for it. But for better extraction, you should specify the list according to application scenarios.

Examples

sentence: Yesterday Bob and his wife got divorced in Guangzhou.
etl: {'Personnel:Elect': ['Person', 'Entity', 'Position', 'Time', 'Place'], 'Business:Declare-Bankruptcy': ['Org', 'Time', 'Place'], 'Justice:Arrest-Jail': ['Person', 'Agent', 'Crime', 'Time', 'Place'], 'Life:Divorce': ['Person', 'Time', 'Place'], 'Life:Injure': ['Agent', 'Victim', 'Instrument', 'Time', 'Place']}
ouptut:
ouptut

sentence: 在2022年卡塔尔世界杯决赛中,阿根廷以点球大战险胜法国。
etl: {'组织行为-罢工': ['时间', '所属组织', '罢工人数', '罢工人员'], '竞赛行为-晋级': ['时间', '晋级方', '晋级赛事'], '财经/交易-涨停':['时间', '涨停股票'] , '组织关系-解雇': ['时间', '解雇方', '被解雇人员']}
ouptut:
ouptut


Setup

  1. Run npm install to download required dependencies.
  2. Run npm run start. GPT4IE should open up in a new browser tab.
  3. note: node-version v14.17.4 npm-version 9.6.0
  4. you need have an Open-AI key.

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