@inproceedings{sun-etal-2017-semantic,
title = "Semantic Dependency Parsing via Book Embedding",
author = "Sun, Weiwei and
Cao, Junjie and
Wan, Xiaojun",
editor = "Barzilay, Regina and
Kan, Min-Yen",
booktitle = "Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = jul,
year = "2017",
address = "Vancouver, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P17-1077/",
doi = "10.18653/v1/P17-1077",
pages = "828--838",
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."
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%0 Conference Proceedings
%T Semantic Dependency Parsing via Book Embedding
%A Sun, Weiwei
%A Cao, Junjie
%A Wan, Xiaojun
%Y Barzilay, Regina
%Y Kan, Min-Yen
%S Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2017
%8 July
%I Association for Computational Linguistics
%C Vancouver, Canada
%F sun-etal-2017-semantic
%X 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.
%R 10.18653/v1/P17-1077
%U https://aclanthology.org/P17-1077/
%U https://doi.org/10.18653/v1/P17-1077
%P 828-838
Markdown (Informal)
[Semantic Dependency Parsing via Book Embedding](https://aclanthology.org/P17-1077/) (Sun et al., ACL 2017)
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.