Awesome Open Source
Awesome Open Source

open-entity-relation-extraction

Knowledge triples extraction (entities and relations extraction) and knowledge base construction based on dependency syntax for open domain text.

基于依存句法分析,实现面向开放域文本的知识三元组抽取(实体和关系抽取)及知识库构建。

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Example

"中国国家主席习近平访问韩国,并在首尔大学发表演讲"

We can extract knowledge triples from the sentence as follows:

  • (中国, 国家主席, 习近平)
  • (习近平, 访问, 韩国)
  • (习近平, 发表演讲, 首尔大学)

Project Structure

knowledge_extraction/
|-- code/  # code directory
|   |-- bean/
|   |-- core/
|   |-- demo/  # procedure entry
|   |-- tool/
|-- data/ # data directory
|   |-- input_text.txt  # input text file
|   |-- knowledge_triple.json  # output knowledge triples file
|-- model/  # ltp models, can be downloaded from http://ltp.ai/download.html, select ltp_data_v3.4.0.zip
|-- resource  # dictionaries dirctory
|-- requirements.txt  # dependent python libraries
|-- README.md  # project description

Requirements

This repo was tested on Python 3.5+. The requirements are:

  • jieba>=0.39
  • pyltp>=0.2.1

Quickstart

cd ./code/demo/
python extract_demo.py

Seven DSNF paradigms

DSNF

References

If you use the code, please kindly cite the following paper:

Jia S, Li M, Xiang Y. Chinese Open Relation Extraction and Knowledge Base Establishment[J]. ACM Transactions on Asian and Low-Resource Language Information Processing (TALLIP), 2018, 17(3): 15.


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