@inproceedings{miller-vosoughi-2020-big,
title = "Big Green at {WNUT} 2020 Shared Task-1: Relation Extraction as Contextualized Sequence Classification",
author = "Miller, Chris and
Vosoughi, Soroush",
editor = "Xu, Wei and
Ritter, Alan and
Baldwin, Tim and
Rahimi, Afshin",
booktitle = "Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020)",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://preview.aclanthology.org/fix-sig-urls/2020.wnut-1.36/",
doi = "10.18653/v1/2020.wnut-1.36",
pages = "281--285",
abstract = "Relation and event extraction is an important task in natural language processing. We introduce a system which uses contextualized knowledge graph completion to classify relations and events between known entities in a noisy text environment. We report results which show that our system is able to effectively extract relations and events from a dataset of wet lab protocols."
}
Markdown (Informal)
[Big Green at WNUT 2020 Shared Task-1: Relation Extraction as Contextualized Sequence Classification](https://preview.aclanthology.org/fix-sig-urls/2020.wnut-1.36/) (Miller & Vosoughi, WNUT 2020)
ACL