Abstract
This paper proposes a general purpose relation extractor that uses Wikidata descriptions to represent the relation’s surface form. The results are tested on the FewRel 1.0 dataset, which provides an excellent framework for training and evaluating the proposed zero-shot learning system in English. This relation extractor architecture exploits the implicit knowledge of a language model through a question-answering approach.- Anthology ID:
- 2020.coling-main.124
- Volume:
- Proceedings of the 28th International Conference on Computational Linguistics
- Month:
- December
- Year:
- 2020
- Address:
- Barcelona, Spain (Online)
- Editors:
- Donia Scott, Nuria Bel, Chengqing Zong
- Venue:
- COLING
- SIG:
- Publisher:
- International Committee on Computational Linguistics
- Note:
- Pages:
- 1447–1451
- Language:
- URL:
- https://aclanthology.org/2020.coling-main.124
- DOI:
- 10.18653/v1/2020.coling-main.124
- Cite (ACL):
- Alberto Cetoli. 2020. Exploring the zero-shot limit of FewRel. In Proceedings of the 28th International Conference on Computational Linguistics, pages 1447–1451, Barcelona, Spain (Online). International Committee on Computational Linguistics.
- Cite (Informal):
- Exploring the zero-shot limit of FewRel (Cetoli, COLING 2020)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2020.coling-main.124.pdf
- Code
- fractalego/fewrel_zero_shot
- Data
- FewRel, SQuAD