Examining crosslingual word sense disambiguation.

Understanding human language computationally remains a challenge at different levels, phonologically, syntactically and semantically. This thesis attempts to understand human language's ambiguity through the Word Sense Disambiguation (WSD) task. Word Sense Disambiguation (WSD) is the task...

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主要作者: Liling, Tan.
其他作者: School of Humanities and Social Sciences
格式: Theses and Dissertations
語言:English
出版: 2013
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spelling sg-ntu-dr.10356-546522019-12-10T13:46:43Z Examining crosslingual word sense disambiguation. Liling, Tan. School of Humanities and Social Sciences SemEval Francis Bond DRNTU::Humanities::Linguistics::Semantics DRNTU::Engineering::Computer science and engineering::Computing methodologies::Document and text processing DRNTU::Engineering::Computer science and engineering::Computer applications::Arts and humanities DRNTU::Engineering::Computer science and engineering::Mathematics of computing::Probability and statistics Understanding human language computationally remains a challenge at different levels, phonologically, syntactically and semantically. This thesis attempts to understand human language's ambiguity through the Word Sense Disambiguation (WSD) task. Word Sense Disambiguation (WSD) is the task of determining the correct sense of a word given a context sentence and topic models are statistical models of human language that can discover abstract topics given a collection of documents. This thesis examines the WSD task in a crosslingual manner with the usage of topic models and parallel corpus. The thesis defines a topical crosslingual WSD (Topical CLWSD) task as two subtasks (i) Match and Translate: finding a match of the query sentence in a parallel corpus using topic models that provides the appropriate translation of the target polysemous word (ii) Map: mapping the word-translation pair to disambiguate the concept respectively of the Open Multilingual WordNet. The XLING WSD system has been built to attempt the topical WSD task. Although the XLING system underperforms in the topical WSD task, it serves as a pilot approach to crosslingual WSD in a knowledge-lean manner. Other than the WSD task, the thesis briefly presents updates on the ongoing work to compile multilingual data for the Nanyang Technological University-Multilingual Corpus (NTU-MC). Both the NTU-MC project and the XLING system are related in their attempts to build crosslingual language technologies. Master of Arts 2013-07-09T00:51:36Z 2013-07-09T00:51:36Z 2013 2013 Thesis http://hdl.handle.net/10356/54652 en 86 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic DRNTU::Humanities::Linguistics::Semantics
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Document and text processing
DRNTU::Engineering::Computer science and engineering::Computer applications::Arts and humanities
DRNTU::Engineering::Computer science and engineering::Mathematics of computing::Probability and statistics
spellingShingle DRNTU::Humanities::Linguistics::Semantics
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Document and text processing
DRNTU::Engineering::Computer science and engineering::Computer applications::Arts and humanities
DRNTU::Engineering::Computer science and engineering::Mathematics of computing::Probability and statistics
Liling, Tan.
Examining crosslingual word sense disambiguation.
description Understanding human language computationally remains a challenge at different levels, phonologically, syntactically and semantically. This thesis attempts to understand human language's ambiguity through the Word Sense Disambiguation (WSD) task. Word Sense Disambiguation (WSD) is the task of determining the correct sense of a word given a context sentence and topic models are statistical models of human language that can discover abstract topics given a collection of documents. This thesis examines the WSD task in a crosslingual manner with the usage of topic models and parallel corpus. The thesis defines a topical crosslingual WSD (Topical CLWSD) task as two subtasks (i) Match and Translate: finding a match of the query sentence in a parallel corpus using topic models that provides the appropriate translation of the target polysemous word (ii) Map: mapping the word-translation pair to disambiguate the concept respectively of the Open Multilingual WordNet. The XLING WSD system has been built to attempt the topical WSD task. Although the XLING system underperforms in the topical WSD task, it serves as a pilot approach to crosslingual WSD in a knowledge-lean manner. Other than the WSD task, the thesis briefly presents updates on the ongoing work to compile multilingual data for the Nanyang Technological University-Multilingual Corpus (NTU-MC). Both the NTU-MC project and the XLING system are related in their attempts to build crosslingual language technologies.
author2 School of Humanities and Social Sciences
author_facet School of Humanities and Social Sciences
Liling, Tan.
format Theses and Dissertations
author Liling, Tan.
author_sort Liling, Tan.
title Examining crosslingual word sense disambiguation.
title_short Examining crosslingual word sense disambiguation.
title_full Examining crosslingual word sense disambiguation.
title_fullStr Examining crosslingual word sense disambiguation.
title_full_unstemmed Examining crosslingual word sense disambiguation.
title_sort examining crosslingual word sense disambiguation.
publishDate 2013
url http://hdl.handle.net/10356/54652
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