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http://dx.doi.org/10.3745/KIPSTB.2010.17B.1.085

Two-Phase Shallow Semantic Parsing based on Partial Syntactic Parsing  

Park, Kyung-Mi (숭실대학교 정보미디어기술연구소)
Mun, Young-Song (숭실대학교 컴퓨터학부)
Publication Information
The KIPS Transactions:PartB / v.17B, no.1, 2010 , pp. 85-92 More about this Journal
Abstract
A shallow semantic parsing system analyzes the relationship that a syntactic constituent of the sentence has with a predicate. It identifies semantic arguments representing agent, patient, instrument, etc. of the predicate. In this study, we propose a two-phase shallow semantic parsing model which consists of the identification phase and the classification phase. We first find the boundary of semantic arguments from partial syntactic parsing results, and then assign appropriate semantic roles to the identified semantic arguments. By taking the sequential two-phase approach, we can alleviate the unbalanced class distribution problem, and select the features appropriate for each task. Experiments show the relative contribution of each phase on the test data.
Keywords
Partial Syntactic Parsing; Shallow Semantic Parsing; Support Vector Machine; Semantic Argument Identification; Semantic Role Assignment;
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