Abstract
Hypernymy modeling has largely been separated according to two paradigms, pattern-based methods and distributional methods. However, recent works utilizing a mix of these strategies have yielded state-of-the-art results. This paper evaluates the contribution of both paradigms to hybrid success by evaluating the benefits of hybrid treatment of baseline models from each paradigm. Even with a simple methodology for each individual system, utilizing a hybrid approach establishes new state-of-the-art results on two domain-specific English hypernym discovery tasks and outperforms all non-hybrid approaches in a general English hypernym discovery task.- Anthology ID:
- P19-1327
- Volume:
- Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2019
- Address:
- Florence, Italy
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 3362–3367
- Language:
- URL:
- https://aclanthology.org/P19-1327
- DOI:
- 10.18653/v1/P19-1327
- Cite (ACL):
- William Held and Nizar Habash. 2019. The Effectiveness of Simple Hybrid Systems for Hypernym Discovery. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 3362–3367, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- The Effectiveness of Simple Hybrid Systems for Hypernym Discovery (Held & Habash, ACL 2019)
- PDF:
- https://preview.aclanthology.org/remove-xml-comments/P19-1327.pdf
- Data
- SemEval-2018 Task 9: Hypernym Discovery