An Analysis of Simple Data Augmentation for Named Entity Recognition

This repository has a pytorch implementation of data augmentation for NER, introduced in our COLING 2020 paper:

Xiang Dai and Heike Adel. 2020. An Analysis of Simple Data Augmentation for Named Entity Recognition. In COLING, Online.

Please cite this paper if you use this code. The paper can be found at the ACL Anthology or at ArXiv.

Purpose of this Software

This software is a research prototype, solely developed for and published as part of the publication cited above. It will neither be maintained nor monitored in any way.

Prepare the i2b2-2010 dataset

Note that the given dataset in data/ contains only sample files, showing the needed format

cp /data/dai031/Experiments/2020-06-03-01/50/* data/

Experiments

No augmentation

python main.py --data_folder data --embedding_type bert --pretrained_dir /data/dai031/Corpora/SciBERT/scibert_scivocab_cased --result_filepath baseline.json

Label-wise token replacement

python main.py --data_folder data --embedding_type bert --pretrained_dir /data/dai031/Corpora/SciBERT/scibert_scivocab_cased --augmentation LwTR --result_filepath lwtr.json

Synonym replacement

python main.py --data_folder data --embedding_type bert --pretrained_dir /data/dai031/Corpora/SciBERT/scibert_scivocab_cased --augmentation SR --result_filepath sr.json

Mention replacement

python main.py --data_folder data --embedding_type bert --pretrained_dir /data/dai031/Corpora/SciBERT/scibert_scivocab_cased --augmentation MR --result_filepath mr.json

Shuffle within segments

python main.py --data_folder data --embedding_type bert --pretrained_dir /data/dai031/Corpora/SciBERT/scibert_scivocab_cased --augmentation SiS --result_filepath sis.json

All

python main.py --data_folder data --embedding_type bert --pretrained_dir /data/dai031/Corpora/SciBERT/scibert_scivocab_cased --augmentation MR LwTR SiS SR --result_filepath all.json

Results

License

The code in this repository is open-sourced under the Apache 2.0 license. See the LICENSE file for details. For a list of other open source components included in this project, see the file 3rd-party-licenses.txt.