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Chinese Open Entity Relation Extraction

Extraction 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
|-- resource  # dictionaries dirctory
|-- requirements.txt  # dependent python libraries
|-- README.md  # project description

Development environment

  • Ubuntu 16.04
  • Python 3.6

Install Dependent libraries

pip install -r requirements.txt

Entry procedure

cd ./code/demo/
python extract_demo.py

Main Implementation Content

DSNF

Paper Cite

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.