Results of the WNUT2017 Shared Task on Novel and Emerging Entity Recognition

Leon Derczynski, Eric Nichols, Marieke van Erp, Nut Limsopatham


Abstract
This shared task focuses on identifying unusual, previously-unseen entities in the context of emerging discussions. Named entities form the basis of many modern approaches to other tasks (like event clustering and summarization), but recall on them is a real problem in noisy text - even among annotators. This drop tends to be due to novel entities and surface forms. Take for example the tweet “so.. kktny in 30 mins?!” – even human experts find the entity ‘kktny’ hard to detect and resolve. The goal of this task is to provide a definition of emerging and of rare entities, and based on that, also datasets for detecting these entities. The task as described in this paper evaluated the ability of participating entries to detect and classify novel and emerging named entities in noisy text.
Anthology ID:
W17-4418
Volume:
Proceedings of the 3rd Workshop on Noisy User-generated Text
Month:
September
Year:
2017
Address:
Copenhagen, Denmark
Editors:
Leon Derczynski, Wei Xu, Alan Ritter, Tim Baldwin
Venue:
WNUT
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
140–147
Language:
URL:
https://aclanthology.org/W17-4418
DOI:
10.18653/v1/W17-4418
Bibkey:
Cite (ACL):
Leon Derczynski, Eric Nichols, Marieke van Erp, and Nut Limsopatham. 2017. Results of the WNUT2017 Shared Task on Novel and Emerging Entity Recognition. In Proceedings of the 3rd Workshop on Noisy User-generated Text, pages 140–147, Copenhagen, Denmark. Association for Computational Linguistics.
Cite (Informal):
Results of the WNUT2017 Shared Task on Novel and Emerging Entity Recognition (Derczynski et al., WNUT 2017)
Copy Citation:
PDF:
https://aclanthology.org/W17-4418.pdf
Data
WNUT 2017IPM NEL