openue: A Python repository from bizhen46766

OpenUE is a toolkit that provides a off-the-shelf framework to implement lots of NLP extraction tasks.

OpenUE allows users ranging from beginner python coders to experienced machine learning engineers to leverage lots of NLP extraction tasks in one easy-to-use python package.

Key Features

Full Guides and API Documentation
Unified API for NLP Tasks with SOTA Pretrained Models (Adaptable with BERT, XLNet, etc.)
- Entity and Realation Extraction
- Intent and Slot Filling
- Event Extraction
- More in development
Training and Inference Interface
Rapid NLP Model Deployment
Dockerizing OpenUE with GPUs
- Easily build and run OpenUE containers leveraging NVIDIA GPUs with Docker

Environment

python3.6
requirements.txt

Quick Start

Requirements and Installation

Anaconda Environment

conda create -n openue python=3.6
conda activate openue
conda install  --file requirements.txt

Examples and General Use

Once you have installed OpenUE, here are a few examples of what you can run with OpenUE modules:

Entity and Relation Extraction Example

Data Preprocessing. Put the pretrined language model (e.g., BERT) in the pretrained_model folder and put all raw data (run script download_ske.sh in the benchmark folder) in the raw_data folder, run

sh download_ske_dataset.sh
sh download_bert_cn.sh
sh preprocess.sh  ske

Train Sequence Labeling & Classification Model. Set all parameters in the file config.py and run

sh train_seq.sh ske
sh train_class.sh ske

Test & Evaluation. Run

python predict.sh ske

Export & Serving. Run

sh export_seq.sh ske
sh serving_cls.sh ske
sh serving.sh

Interactive Prediction. Run

python  predict_online.py

Demo.Run

python app.py  ske

Tools

>>> import openuee
>>> model = openue.get_model('ske_bert_entity_relation')
>>> res = model.infer('《上海滩》是刘德华的音乐作品，黄沾作曲，收录在《【歌单】酷我热门单曲合辑》专辑中')
>>> print(res)
"spo_list": [{"object_type": "人物", "predicate": "作曲", "object": "黄沾", "subject_type": "歌曲", "subject": "上海滩"}, {"object_type": "音乐专辑", "predicate": "所属专辑", "object": "【歌单】酷我热门单曲合辑", "subject_type": "歌曲", "subject": "上海滩"}, {"object_type": "人物", "predicate": "歌手", "object": "刘德华", "subject_type": "歌曲", "subject": "上海滩"}]

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 Toolkit of Universal Extraction from Text",
    author = "Ningyu Zhang, Shumin Deng, Zhen Bi, Haiyang Yu, Jiacheng Yang, Mosha Chen, Fei Huang, Wei Zhang, Huajun Chen",
    year = "2020",
}

bizhen46766/openue