Abstract
We design, implement and evaluate two semantic parsers, which represent factorization- and composition-based approaches respectively, for Elementary Dependency Structures (EDS) at the CoNLL 2019 Shared Task on Cross-Framework Meaning Representation Parsing. The detailed evaluation of the two parsers gives us a new perception about parsing into linguistically enriched meaning representations: current neural EDS parsers are able to reach an accuracy at the inter-annotator agreement level in the same-epoch-and-domain setup.- Anthology ID:
- K19-2016
- Volume:
- Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning
- Month:
- November
- Year:
- 2019
- Address:
- Hong Kong
- Venue:
- CoNLL
- SIG:
- SIGNLL
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 166–176
- Language:
- URL:
- https://aclanthology.org/K19-2016
- DOI:
- 10.18653/v1/K19-2016
- Cite (ACL):
- Yufei Chen, Yajie Ye, and Weiwei Sun. 2019. Peking at MRP 2019: Factorization- and Composition-Based Parsing for Elementary Dependency Structures. In Proceedings of the Shared Task on Cross-Framework Meaning Representation Parsing at the 2019 Conference on Natural Language Learning, pages 166–176, Hong Kong. Association for Computational Linguistics.
- Cite (Informal):
- Peking at MRP 2019: Factorization- and Composition-Based Parsing for Elementary Dependency Structures (Chen et al., CoNLL 2019)
- PDF:
- https://preview.aclanthology.org/starsem-semeval-split/K19-2016.pdf