Abstract
The Penn Treebank (PTB) represents syntactic structures as graphs due to nonlocal dependencies. This paper proposes a method that approximates PTB graph-structured representations by trees. By our approximation method, we can reduce nonlocal dependency identification and constituency parsing into single tree-based parsing. An experimental result demonstrates that our approximation method with an off-the-shelf tree-based constituency parser significantly outperforms the previous methods in nonlocal dependency identification.- Anthology ID:
- P19-1530
- Volume:
- Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Anna Korhonen, David Traum, Lluís Màrquez
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 5344–5349
- Language:
- URL:
- https://aclanthology.org/P19-1530
- DOI:
- 10.18653/v1/P19-1530
- Cite (ACL):
- Yoshihide Kato and Shigeki Matsubara. 2019. PTB Graph Parsing with Tree Approximation. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 5344–5349, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- PTB Graph Parsing with Tree Approximation (Kato & Matsubara, ACL 2019)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-5/P19-1530.pdf
- Code
- yosihide/ptb2cf
- Data
- Penn Treebank