# ChEMU-Ref: A Corpus for Modeling Anaphora Resolution in the Chemical Domain

Published:

Biaoyan Fang, Christian Druckenbrodt, Saber A Akhondi, Jiayuan He, Timothy Baldwin and Karin Verspoor (2021) ChEMU-Ref: A Corpus for Modeling Anaphora Resolution in the Chemical Domain. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics (EACL2021), virtual conference, pp. 1362–1375.

@inproceedings{fang-etal-2021-chemu,
title = "{C}h{EMU}-Ref: A Corpus for Modeling Anaphora Resolution in the Chemical Domain",
author = "Fang, Biaoyan  and
Druckenbrodt, Christian  and
Akhondi, Saber A  and
He, Jiayuan  and
Baldwin, Timothy  and
Verspoor, Karin",
booktitle = "Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume",
month = apr,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.eacl-main.116",
pages = "1362--1375",
abstract = "Chemical patents contain rich coreference and bridging links, which are the target of this research. Specially, we introduce a novel annotation scheme, based on which we create the ChEMU-Ref dataset from reaction description snippets in English-language chemical patents. We propose a neural approach to anaphora resolution, which we show to achieve strong results, especially when jointly trained over coreference and bridging links.",
}


## Abstract

Chemical patents contain rich coreference and bridging links, which are the target of this research. Specially, we introduce a novel annotation scheme, based on which we create the ChEMU-Ref dataset from reaction description snippets in English-language chemical patents. We propose a neural approach to anaphora resolution, which we show to achieve strong results, especially when jointly trained over coreference and bridging links.