Expert-built and collaboratively constructed lexical semantic resources

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Expert-built and collaboratively constructed lexical semantic resources
Authors: Iryna Gurevych, Elisabeth Wolf [edit item]
Citation: Language and Linguistics Compass 4 (11): 1074-1090. 2010.
Publication type: Journal article
Peer-reviewed: Yes
Database(s):
DOI: 10.1111/j.1749-818X.2010.00251.x.
Google Scholar cites: Citations
Link(s): Paper link
Added by Wikilit team: Added on initial load
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Expert-built and collaboratively constructed lexical semantic resources is a publication by Iryna Gurevych, Elisabeth Wolf.


[edit] Abstract

Knowledge about words, their meanings, and their relations to other words contained in lexical semantic resources is of particular interest for the automatic processing of human language. In the last decades, expert-built lexical semantic resources such as WordNet have been utilized in a vast number of natural language processing (NLP) tasks. Recently, collaboratively constructed resources such as the online encyclopedia Wikipedia with its exceptional scale and Wiktionary, a combination of dictionary and thesaurus, have been discovered as valuable substitutes for expert-built resources. In this study, we first introduce diverse types of lexical semantic resources with respect to their content and structure. We identify the differences between expert-built and collaboratively constructed resources and compare WordNet, Wiktionary, and Wikipedia. We provide a comprehensive overview of the lexical semantic knowledge therein and discuss their assets and drawbacks. Finally, we review work on orchestrating different resources in order to combine their strengths and explore their use in major NLP applications.

[edit] Research questions

"In this study, we introduce different types of lexical semantic resources (LSRs) that capture lexical semantic information about the content and structure of words. We distinguish between conventional LSRs and resources created collaboratively by ordinary web users. We discuss and compare some of the major resources, i.e. WordNet, Wiktionary, and Wikipedia, with respect to the lexical semantic knowledge therein, and analyze their assets and drawbacks. Finally, we review work on orchestrating different resources in order to combine their strengths and examine the use of LSRs in core NLP applications."

Research details

Topics: Computational linguistics [edit item]
Domains: Computer science [edit item]
Theory type: Analysis [edit item]
Wikipedia coverage: Case [edit item]
Theories: "Undetermined" [edit item]
Research design: Case study [edit item]
Data source: Websites [edit item]
Collected data time dimension: Cross-sectional [edit item]
Unit of analysis: Website [edit item]
Wikipedia data extraction: Live Wikipedia [edit item]
Wikipedia page type: Article, Information categorization and navigation [edit item]
Wikipedia language: English [edit item]

[edit] Conclusion

"In this study, we introduced diverse types of LSRs and identified and discussed the major differences between expert-built and collaboratively constructed LSRs. For comparison, we chose WordNet, an instance of an expert-built LSR, and Wiktionary as its collaboratively constructed correspondent. Furthermore, we analyzed Wikipedia and provided a comprehensive overview of the encoded lexical semantic knowledge therein. It turned out that both Wiktionary and Wikipedia are emerging resources for various NLP tasks as they perform competitively to expert-built LSRs when used as a source of lexical semantic knowledge. We reviewed some recent works, which aim at aligning ELSRs and CLSRs and briefly described major NLP tasks in which these resources are utilized."

[edit] Comments

"It turned out that both Wiktionary and Wikipedia are emerging resources for various NLP tasks as they perform competitively to expert-built LSRs when used as a source of lexical semantic knowledge."


Further notes[edit]

Facts about "Expert-built and collaboratively constructed lexical semantic resources"RDF feed
AbstractKnowledge about words, their meanings, andKnowledge about words, their meanings, and their relations to other words contained in lexical semantic resources is of particular interest for the automatic processing of human language. In the last decades, expert-built lexical semantic resources such as WordNet have been utilized in a vast number of natural language processing (NLP) tasks. Recently, collaboratively constructed resources such as the online encyclopedia Wikipedia with its exceptional scale and Wiktionary, a combination of dictionary and thesaurus, have been discovered as valuable substitutes for expert-built resources. In this study, we first introduce diverse types of lexical semantic resources with respect to their content and structure. We identify the differences between expert-built and collaboratively constructed resources and compare WordNet, Wiktionary, and Wikipedia. We provide a comprehensive overview of the lexical semantic knowledge therein and discuss their assets and drawbacks. Finally, we review work on orchestrating different resources in order to combine their strengths and explore their use in major NLP applications.plore their use in major NLP applications.
Added by wikilit teamAdded on initial load +
Collected data time dimensionCross-sectional +
CommentsIt turned out that both Wiktionary and Wikipedia are emerging resources for various NLP tasks as they perform competitively to expert-built LSRs when used as a source of lexical semantic knowledge.
ConclusionIn this study, we introduced diverse typesIn this study, we introduced diverse types of LSRs and identified and discussed the major differences between expert-built and collaboratively constructed LSRs. For comparison, we chose WordNet, an instance of an expert-built LSR, and Wiktionary as its collaboratively constructed correspondent. Furthermore, we analyzed Wikipedia and provided a comprehensive overview of the encoded lexical semantic knowledge therein. It turned out that both Wiktionary and Wikipedia are emerging resources for various NLP tasks as they perform competitively to expert-built LSRs when used as a source of lexical semantic knowledge. We reviewed some recent works, which aim at aligning ELSRs and CLSRs and briefly described major NLP tasks in which these resources are utilized.sks in which these resources are utilized.
Data sourceWebsites +
Doi10.1111/j.1749-818X.2010.00251.x +
Google scholar urlhttp://scholar.google.com/scholar?ie=UTF-8&q=%22Expert-built%2Band%2Bcollaboratively%2Bconstructed%2Blexical%2Bsemantic%2Bresources%22 +
Has authorIryna Gurevych + and Elisabeth Wolf +
Has domainComputer science +
Has topicComputational linguistics +
Issue11 +
Pages1074-1090 +
Peer reviewedYes +
Publication typeJournal article +
Published inLanguage and Linguistics Compass +
Research designCase study +
Research questionsIn this study, we introduce different typeIn this study, we introduce different types of lexical semantic resources (LSRs) that capture lexical semantic information about the content and structure of words. We distinguish between conventional LSRs and resources created collaboratively by ordinary web users. We discuss and compare some of the major resources, i.e. WordNet, Wiktionary, and Wikipedia, with respect to the lexical semantic knowledge therein, and analyze their assets and drawbacks. Finally, we review work on orchestrating different resources in order to combine their strengths and examine the use of LSRs in core NLP applications. the use of LSRs in core NLP applications.
Revid10,757 +
TheoriesUndetermined
Theory typeAnalysis +
TitleExpert-built and collaboratively constructed lexical semantic resources
Unit of analysisWebsite +
Urlhttp://doi.wiley.com/10.1111/j.1749-818X.2010.00251.x +
Volume4 +
Wikipedia coverageCase +
Wikipedia data extractionLive Wikipedia +
Wikipedia languageEnglish +
Wikipedia page typeArticle + and Information categorization and navigation +
Year2010 +