Trained BERT models for phrase alignment with the constrained tree edit distance algorithm
Description
These are the trained BERT models for phrase alignment with the constrained tree edit distance algorithm, published at EMNLP2020.
Yuki Arase and Jun'ichi Tsujii. 2020. Compositional Phrase Alignment and Beyond. in Proc. of the Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1611-1623.
Source codes are available at GitHub
When you use these models, please cite the following paper.
@inproceedings{arase-tsujii-2020-compositional,
title = "Compositional Phrase Alignment and Beyond",
author = "Arase, Yuki and
Tsujii, Jun{'}ichi",
booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/2020.emnlp-main.125",
doi = "10.18653/v1/2020.emnlp-main.125",
pages = "1611--1623"
}
Files
Files
(1.4 GB)
Name | Size | Download all |
---|---|---|
md5:bb2ed499d227a633b0a684961059d73b
|
452.2 MB | Download |
md5:dde7660fa19a4482a2c552097b3c2723
|
464.8 MB | Download |
md5:64843ac471b34988954b87b94d814097
|
438.0 MB | Download |