Abstract
With the development of several multilingual datasets used for semantic parsing, recent research efforts have looked into the problem of learning semantic parsers in a multilingual setup. However, how to improve the performance of a monolingual semantic parser for a specific language by leveraging data annotated in different languages remains a research question that is under-explored. In this work, we present a study to show how learning distributed representations of the logical forms from data annotated in different languages can be used for improving the performance of a monolingual semantic parser. We extend two existing monolingual semantic parsers to incorporate such cross-lingual distributed logical representations as features. Experiments show that our proposed approach is able to yield improved semantic parsing results on the standard multilingual GeoQuery dataset.- Anthology ID:
- P18-2107
- Volume:
- Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
- Month:
- July
- Year:
- 2018
- Address:
- Melbourne, Australia
- Editors:
- Iryna Gurevych, Yusuke Miyao
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 673–679
- Language:
- URL:
- https://aclanthology.org/P18-2107
- DOI:
- 10.18653/v1/P18-2107
- Cite (ACL):
- Yanyan Zou and Wei Lu. 2018. Learning Cross-lingual Distributed Logical Representations for Semantic Parsing. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 673–679, Melbourne, Australia. Association for Computational Linguistics.
- Cite (Informal):
- Learning Cross-lingual Distributed Logical Representations for Semantic Parsing (Zou & Lu, ACL 2018)
- PDF:
- https://preview.aclanthology.org/teach-a-man-to-fish/P18-2107.pdf