openue 0.0.2

Universal extractor for text.

OpenUE

OpenUE is an open-source and extensible toolkit that provides a off-the-shelf framework to implement a plethora of extraction tasks.

You can refer to our document for more details about this project.

Getting Started

Requirement

conda -r openue

python -r requirement.txt

sh preprocess

sh train_

sh predict.sh

python gen_triple.py

#Serving

Joint Entity and Relation Extraction

table

Joint Slot Filing and Intent Classification

table

Joint Opinion and Sentiment Classification

table

Install

Install as A Python Package

We are now working on deploy OpenUE as a Python package. Coming soon!

Using Git Repository

Clone the repository from our github page (don't forget to star us!)

git clone https://github.com/zxlzr/OpenUE.git

If it is too slow, you can try

git clone https://github.com/zxlzr/OpenUE.git --depth 1

Then install all the requirements:

pip install -r requirements.txt

Then install the package with

python setup.py install 

Tools

>>> import openuee
>>> model = openue.get_model('ske_bert_entity_relation')

Note that it may take a few minutes to download checkpoint and data for the first time. Then use infer to do sentence-level entity and relation extraction

## How to Cite

If you use or extend our work, please cite the following paper:

@inproceedings{zhang-2020-opennue, title = "{O}pe{UE}: An Open and Extensible Toolkit for Universal Extraction in Text", author = "Ningyu Zhang, Shumin Deng, Huajun Chen", year = "2020", }