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Incorporating Frame Information to Semantic Role Labeling

Authors
Lee, Joo-YoungSong, Young-InRim, Hae-ChangHan, Kyoung-Soo
Issue Date
Jan-2010
Publisher
IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG
Keywords
semantic role labeling; predicate-argument structure; frame information; propbank; frameset
Citation
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, v.E93D, no.1, pp.201 - 204
Indexed
SCIE
SCOPUS
Journal Title
IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS
Volume
E93D
Number
1
Start Page
201
End Page
204
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/117290
DOI
10.1587/transinf.E93.D.201
ISSN
0916-8532
Abstract
In this paper, we suggest a new probabilistic model of semantic role labeling, which uses the frameset of the predicate as explicit linguistic knowledge for providing global information on the predicate-argument structure that local classifier is unable to catch. The proposed model consists of three sub-models: role sequence generation model, frameset generation model, and matching model. The role sequence generation model generates the semantic role sequence candidates of a given predicate by using the local classification approach, which is a widely used approach in previous research. The frameset generation model estimates the probability of each frameset that the predicate can take. The matching model is designed to measure the degree of the matching between the generated role sequence and the frameset by using several features. These features are developed to represent the predicate-argument structure information described in the frameset. In the experiments, our model shows that the use of knowledge about the predicate-argument structure is effective for selecting a more appropriate semantic role sequence.
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