Frame-Based Continuous Lexical Semantics through Exponential Family Tensor Factorization and Semantic Proto-Roles
Francis Ferraro, Adam Poliak, Ryan Cotterell, Benjamin Van Durme
Abstract
We study how different frame annotations complement one another when learning continuous lexical semantics. We learn the representations from a tensorized skip-gram model that consistently encodes syntactic-semantic content better, with multiple 10% gains over baselines.- Anthology ID:
- S17-1011
- Volume:
- Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017)
- Month:
- August
- Year:
- 2017
- Address:
- Vancouver, Canada
- Editors:
- Nancy Ide, Aurélie Herbelot, Lluís Màrquez
- Venue:
- *SEM
- SIGs:
- SIGLEX | SIGSEM
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 97–103
- Language:
- URL:
- https://aclanthology.org/S17-1011
- DOI:
- 10.18653/v1/S17-1011
- Cite (ACL):
- Francis Ferraro, Adam Poliak, Ryan Cotterell, and Benjamin Van Durme. 2017. Frame-Based Continuous Lexical Semantics through Exponential Family Tensor Factorization and Semantic Proto-Roles. In Proceedings of the 6th Joint Conference on Lexical and Computational Semantics (*SEM 2017), pages 97–103, Vancouver, Canada. Association for Computational Linguistics.
- Cite (Informal):
- Frame-Based Continuous Lexical Semantics through Exponential Family Tensor Factorization and Semantic Proto-Roles (Ferraro et al., *SEM 2017)
- PDF:
- https://preview.aclanthology.org/improve-issue-templates/S17-1011.pdf
- Code
- fmof/tensor-factorization
- Data
- FrameNet