PP-attachment disambiguation boosted by a gigantic volume of unambiguous examples

Daisuke Kawahara; Sadao Kurohashi

doi:10.1007/11562214_17

PP-attachment disambiguation boosted by a gigantic volume of unambiguous examples

Daisuke Kawahara^*, Sadao Kurohashi

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Citations (Scopus)

Abstract

We present a PP-attachment disambiguation method based on a gigantic volume of unambiguous examples extracted from raw corpus. The unambiguous examples are utilized to acquire precise lexical preferences for PP-attachment disambiguation. Attachment decisions are made by a machine learning method that optimizes the use of the lexical preferences. Our experiments indicate that the precise lexical preferences work effectively.

Original language	English
Title of host publication	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages	188-198
Number of pages	11
DOIs	https://doi.org/10.1007/11562214_17
Publication status	Published - 2005
Externally published	Yes
Event	2nd International Joint Conference on Natural Language Processing, IJCNLP 2005 - Jeju Island, Korea, Republic of Duration: 2005 Oct 11 → 2005 Oct 13

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3651 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	2nd International Joint Conference on Natural Language Processing, IJCNLP 2005
Country/Territory	Korea, Republic of
City	Jeju Island
Period	05/10/11 → 05/10/13

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

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10.1007/11562214_17

Cite this

Kawahara, D., & Kurohashi, S. (2005). PP-attachment disambiguation boosted by a gigantic volume of unambiguous examples. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 188-198). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3651 LNAI). https://doi.org/10.1007/11562214_17

PP-attachment disambiguation boosted by a gigantic volume of unambiguous examples. / Kawahara, Daisuke; Kurohashi, Sadao.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2005. p. 188-198 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3651 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kawahara, D & Kurohashi, S 2005, PP-attachment disambiguation boosted by a gigantic volume of unambiguous examples. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3651 LNAI, pp. 188-198, 2nd International Joint Conference on Natural Language Processing, IJCNLP 2005, Jeju Island, Korea, Republic of, 05/10/11. https://doi.org/10.1007/11562214_17

Kawahara D, Kurohashi S. PP-attachment disambiguation boosted by a gigantic volume of unambiguous examples. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2005. p. 188-198. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/11562214_17

Kawahara, Daisuke ; Kurohashi, Sadao. / PP-attachment disambiguation boosted by a gigantic volume of unambiguous examples. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 2005. pp. 188-198 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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PP-attachment disambiguation boosted by a gigantic volume of unambiguous examples

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