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:
- 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)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/2020.lrec-1.548.pdf
- Code
- HKUST-KnowComp/cfet