Semantic Dependency Parsing via Book Embedding

Weiwei Sun, Junjie Cao, Xiaojun Wan


Abstract
We model a dependency graph as a book, a particular kind of topological space, for semantic dependency parsing. The spine of the book is made up of a sequence of words, and each page contains a subset of noncrossing arcs. To build a semantic graph for a given sentence, we design new Maximum Subgraph algorithms to generate noncrossing graphs on each page, and a Lagrangian Relaxation-based algorithm tocombine pages into a book. Experiments demonstrate the effectiveness of the bookembedding framework across a wide range of conditions. Our parser obtains comparable results with a state-of-the-art transition-based parser.
Anthology ID:
P17-1077
Volume:
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Month:
July
Year:
2017
Address:
Vancouver, Canada
Editors:
Regina Barzilay, Min-Yen Kan
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
828–838
Language:
URL:
https://aclanthology.org/P17-1077
DOI:
10.18653/v1/P17-1077
Bibkey:
Cite (ACL):
Weiwei Sun, Junjie Cao, and Xiaojun Wan. 2017. Semantic Dependency Parsing via Book Embedding. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 828–838, Vancouver, Canada. Association for Computational Linguistics.
Cite (Informal):
Semantic Dependency Parsing via Book Embedding (Sun et al., ACL 2017)
Copy Citation:
PDF:
https://aclanthology.org/P17-1077.pdf
Note:
 P17-1077.Notes.pdf
Software:
 P17-1077.Software.tgz
Video:
 https://aclanthology.org/P17-1077.mp4