Simple-Clips ongoing research: more information with less data by implementing inheritance
9553Authors
nan
Abstract
AbstractThis paper presents the application of inheritance to the formal taxonomy (is-a) of a semantically rich Language Resource based on the Generative Lexicon theory, SIMPLE-CLIPS. The aim is to lighten the representation of its semantic layer by reducing the number of encoded relations. A prediction calculation on the impact of introducing inheritance regarding space occupancy is carried out, yielding a significant space reduction of 22%. This is corroborated by its actual application, which reduces the number of explicitly encoded relations in this lexicon by 18.4%. Later on, we study the issues that inheritance poses to the Language Resources, and discuss sensitive solutions to tackle each of them, including examples. Finally, we present a discussion on the application of inheritance, from which two side effect advantages arise: consistency enhancement and inference capabilities.
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nan
Labeled Text
AbstractThis paper presents the application of inheritance to the formal taxonomy (is-a) of a semantically rich Language Resource based on the Generative Lexicon theory, SIMPLE-CLIPS. The aim is to lighten the representation of its semantic layer by reducing the number of encoded relations. A prediction calculation on the impact of introducing inheritance regarding space occupancy is carried out, yielding a significant space reduction of 22%. This is corroborated by its actual application, which reduces the number of explicitly encoded relations in this lexicon by 18.4%. Later on, we study the issues that inheritance poses to the Language Resources, and discuss sensitive solutions to tackle each of them, including examples. Finally, we present a discussion on the application of inheritance, from which two side effect advantages arise: consistency enhancement and inference capabilities.
Publication Details
- Paper ID:
- 9553
- Year:
- 2008
- Publication:
- TIPSTER
- Publication Type:
- conf
- DOI:
- nan