Mapping WordNet to a relational network

Jonathan J. Webster; Ian C. Chow

doi:10.1109/NLPKE.2005.1598830

Mapping WordNet to a relational network

Jonathan J. Webster, Ian C. Chow

City University of Hong Kong

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

4 Citations (Scopus)

Abstract

This paper discusses the implementation of a lexical knowledge base, based on a conceptualization of the problem domain in terms of Relational Network Notation [7]. In particular, we focus here on the importing of lemmas as instances from WordNet 2.0 into the knowledge base. Relational Network Notation (RNN) offers a simple yet powerful means for representing lexicogrammatical, semantic and sememic information. RNN is driven by Relational Network Theory [4][5][6] and incorporates developments in the theory which have been shown to not only describe but also explain linguistic phenomena in a neurologically plausible manner. © 2005 IEEE.

Original language	English
Title of host publication	Proceedings of 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering, IEEE NLP-KE'05
Pages	718-722
Volume	2005
DOIs	https://doi.org/10.1109/NLPKE.2005.1598830
Publication status	Published - 2005
Event	2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering, IEEE NLP-KE'05 - Wuhan, China Duration: 30 Oct 2005 → 1 Nov 2005

Publication series

Name
Volume	2005

Conference

Conference	2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering, IEEE NLP-KE'05
Country/Territory	China
City	Wuhan
Period	30/10/05 → 1/11/05

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title = "Mapping WordNet to a relational network",

abstract = "This paper discusses the implementation of a lexical knowledge base, based on a conceptualization of the problem domain in terms of Relational Network Notation [7]. In particular, we focus here on the importing of lemmas as instances from WordNet 2.0 into the knowledge base. Relational Network Notation (RNN) offers a simple yet powerful means for representing lexicogrammatical, semantic and sememic information. RNN is driven by Relational Network Theory [4][5][6] and incorporates developments in the theory which have been shown to not only describe but also explain linguistic phenomena in a neurologically plausible manner. {\textcopyright} 2005 IEEE.",

author = "Webster, {Jonathan J.} and Chow, {Ian C.}",

year = "2005",

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volume = "2005",

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booktitle = "Proceedings of 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering, IEEE NLP-KE'05",

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Webster, JJ & Chow, IC 2005, Mapping WordNet to a relational network. in Proceedings of 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering, IEEE NLP-KE'05. vol. 2005, 1598830, pp. 718-722, 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering, IEEE NLP-KE'05, Wuhan, China, 30/10/05. https://doi.org/10.1109/NLPKE.2005.1598830

Mapping WordNet to a relational network. / Webster, Jonathan J.; Chow, Ian C.
Proceedings of 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering, IEEE NLP-KE'05. Vol. 2005 2005. p. 718-722 1598830.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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AB - This paper discusses the implementation of a lexical knowledge base, based on a conceptualization of the problem domain in terms of Relational Network Notation [7]. In particular, we focus here on the importing of lemmas as instances from WordNet 2.0 into the knowledge base. Relational Network Notation (RNN) offers a simple yet powerful means for representing lexicogrammatical, semantic and sememic information. RNN is driven by Relational Network Theory [4][5][6] and incorporates developments in the theory which have been shown to not only describe but also explain linguistic phenomena in a neurologically plausible manner. © 2005 IEEE.

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DO - 10.1109/NLPKE.2005.1598830

M3 - RGC 32 - Refereed conference paper (with host publication)

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VL - 2005

SP - 718

EP - 722

BT - Proceedings of 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering, IEEE NLP-KE'05

T2 - 2005 IEEE International Conference on Natural Language Processing and Knowledge Engineering, IEEE NLP-KE'05

Y2 - 30 October 2005 through 1 November 2005

ER -

Mapping WordNet to a relational network

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