Learning Cross-lingual Distributed Logical Representations for Semantic Parsing

Yanyan Zou, Wei Lu


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
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
Bibkey:
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)
Copy Citation:
PDF:
https://preview.aclanthology.org/author-url/P18-2107.pdf
Presentation:
 P18-2107.Presentation.pdf
Video:
 https://vimeo.com/285805938