Two-Phase S-Clause Segmentation
Summary :
When a dependency parser analyzes long sentences with fewer subjects than predicates, it is difficult for it to recognize which predicate governs which subject. To handle such syntactic ambiguity between subjects and predicates, we define an "a subject clause (s-clause)" as a group of words containing several predicates and their common subject. This paper proposes a two-phase method for S-clause segmentation. The first phase reduces the number of candidates of S-clause boundaries, and the second performs S-clause segmentation using decision trees. In experimental evaluation, the S-clause information turned out to be effective for determining the governor of a subject and that of a predicate in dependency parsing. Further syntactic analysis using S-clauses achieved an improvement in precision of 5 percent.
- Publication
- IEICE TRANSACTIONS on Information Vol.E88-D No.7 pp.1724-1736
- Publication Date
- 2005/07/01
- Publicized
- Online ISSN
- DOI
- 10.1093/ietisy/e88-d.7.1724
- Type of Manuscript
- PAPER
- Category
- Natural Language Processing
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Keyword
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Mi-Young KIM, Jong-Hyeok LEE, "Two-Phase S-Clause Segmentation" in IEICE TRANSACTIONS on Information,
vol. E88-D, no. 7, pp. 1724-1736, July 2005, doi: 10.1093/ietisy/e88-d.7.1724.
Abstract: When a dependency parser analyzes long sentences with fewer subjects than predicates, it is difficult for it to recognize which predicate governs which subject. To handle such syntactic ambiguity between subjects and predicates, we define an "a subject clause (s-clause)" as a group of words containing several predicates and their common subject. This paper proposes a two-phase method for S-clause segmentation. The first phase reduces the number of candidates of S-clause boundaries, and the second performs S-clause segmentation using decision trees. In experimental evaluation, the S-clause information turned out to be effective for determining the governor of a subject and that of a predicate in dependency parsing. Further syntactic analysis using S-clauses achieved an improvement in precision of 5 percent.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e88-d.7.1724/_p
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@ARTICLE{e88-d_7_1724,
author={Mi-Young KIM, Jong-Hyeok LEE, },
journal={IEICE TRANSACTIONS on Information},
title={Two-Phase S-Clause Segmentation},
year={2005},
volume={E88-D},
number={7},
pages={1724-1736},
abstract={When a dependency parser analyzes long sentences with fewer subjects than predicates, it is difficult for it to recognize which predicate governs which subject. To handle such syntactic ambiguity between subjects and predicates, we define an "a subject clause (s-clause)" as a group of words containing several predicates and their common subject. This paper proposes a two-phase method for S-clause segmentation. The first phase reduces the number of candidates of S-clause boundaries, and the second performs S-clause segmentation using decision trees. In experimental evaluation, the S-clause information turned out to be effective for determining the governor of a subject and that of a predicate in dependency parsing. Further syntactic analysis using S-clauses achieved an improvement in precision of 5 percent.},
keywords={},
doi={10.1093/ietisy/e88-d.7.1724},
ISSN={},
month={July},}
Copy
TY - JOUR
TI - Two-Phase S-Clause Segmentation
T2 - IEICE TRANSACTIONS on Information
SP - 1724
EP - 1736
AU - Mi-Young KIM
AU - Jong-Hyeok LEE
PY - 2005
DO - 10.1093/ietisy/e88-d.7.1724
JO - IEICE TRANSACTIONS on Information
SN -
VL - E88-D
IS - 7
JA - IEICE TRANSACTIONS on Information
Y1 - July 2005
AB - When a dependency parser analyzes long sentences with fewer subjects than predicates, it is difficult for it to recognize which predicate governs which subject. To handle such syntactic ambiguity between subjects and predicates, we define an "a subject clause (s-clause)" as a group of words containing several predicates and their common subject. This paper proposes a two-phase method for S-clause segmentation. The first phase reduces the number of candidates of S-clause boundaries, and the second performs S-clause segmentation using decision trees. In experimental evaluation, the S-clause information turned out to be effective for determining the governor of a subject and that of a predicate in dependency parsing. Further syntactic analysis using S-clauses achieved an improvement in precision of 5 percent.
ER -
English
