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Ordered Tree Decomposition for HRG Rule Extraction

delete2019-06-01
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OA
AI
D
Daniel Gildea *
G
Giorgio Satta
X
Xiaochang Peng
DOI:10.1162/coli_a_00350delete
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摘要

摘要

En 中文
We present algorithms for extracting Hyperedge Replacement Grammar (HRG) rules from a graph along with a vertex order. Our algorithms are based on finding a tree decomposition of smallest width, relative to the vertex order, and then extracting one rule for each node in this structure. The assumption of a fixed order for the vertices of the input graph makes it possible to solve the problem in polynomial time, in contrast to the fact that the problem of finding optimal tree decompositions for a graph is NP-hard. We also present polynomial-time algorithms for parsing based on our HRGs, where the input is a vertex sequence and the output is a graph structure. The intended application of our algorithms is grammar extraction and parsing for semantic representation of natural language. We apply our algorithms to data annotated with Abstract Meaning Representations and report on the characteristics of the resulting grammars.
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期刊

Computational Linguistics 封面图
Computational Linguistics
IF:
5.3
论文数:
837
被引数:
2.7K

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U
University of Padua
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5.1W
论文数: 4.3W
被引数: 57
U
University of Rochester
学者数:
2.6W
论文数: 2.1W
被引数: 2.2W
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