Hierarchical Contextualized Representation for Named Entity Recognition

Codes for the paper Hierarchical Contextualized Representation for Named Entity Recognition in AAAI 2020

Requirement

Python: 3.6 or higher.
PyTorch 0.4.1 or higher.

Usage

Prepare training data and word/label embeddings in sample_data.

In training status: python main.py --config demo.train.config

In test status: python main.py --config demo.test.config

The configuration file controls the network structure, I/O, training setting and hyperparameters.

BERT embeddings

We use the tool to gennerate the BERT embedding for NER.

Models

Our pre-trained model is put in lstmcrf.model.

Citation

If you use this software for research, please cite our paper as follows:

@inproceedings{luo2019hierarchical,
    title={Hierarchical Contextualized Representation for Named Entity Recognition},
    author={Luo, Ying and Xiao, Fengshun and Zhao, Hai},
    booktitle = "the Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-2020)",
    year = "2020",
}

Credits