A Chinese Corpus for Fine-grained Entity Typing

Chin Lee, Hongliang Dai, Yangqiu Song, Xin Li


Abstract
Fine-grained entity typing is a challenging task with wide applications. However, most existing datasets for this task are in English. In this paper, we introduce a corpus for Chinese fine-grained entity typing that contains 4,800 mentions manually labeled through crowdsourcing. Each mention is annotated with free-form entity types. To make our dataset useful in more possible scenarios, we also categorize all the fine-grained types into 10 general types. Finally, we conduct experiments with some neural models whose structures are typical in fine-grained entity typing and show how well they perform on our dataset. We also show the possibility of improving Chinese fine-grained entity typing through cross-lingual transfer learning.
Anthology ID:
2020.lrec-1.548
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
4451–4457
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.548
DOI:
Bibkey:
Cite (ACL):
Chin Lee, Hongliang Dai, Yangqiu Song, and Xin Li. 2020. A Chinese Corpus for Fine-grained Entity Typing. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 4451–4457, Marseille, France. European Language Resources Association.
Cite (Informal):
A Chinese Corpus for Fine-grained Entity Typing (Lee et al., LREC 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.lrec-1.548.pdf
Code
 HKUST-KnowComp/cfet