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Automatic Key Selection for Data Linking Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Framester: A Wide Coverage Linguistic Linked Data Hub

Authors : Aldo Gangemi, Mehwish Alam, Luigi Asprino, Valentina Presutti, Diego Reforgiato Recupero

Published in: Knowledge Engineering and Knowledge Management

Publisher: Springer International Publishing

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Abstract

Semantic web applications leveraging NLP can benefit from easy access to expressive lexical resources such as FrameNet. However, the usefulness of FrameNet is affected by its limited coverage and non-standard semantics. The access to existing linguistic resources is also limited because of poor connectivity among them. We present some strategies based on Linguistic Linked Data to broaden FrameNet coverage and formal linkage of lexical and factual resources. We created a novel resource, Framester, which acts as a hub between FrameNet, WordNet, VerbNet, BabelNet, DBpedia, Yago, DOLCE-Zero, as well as other resources. Framester is not only a strongly connected knowledge graph, but also applies a rigorous formal treatment for Fillmore’s frame semantics, enabling full-fledged OWL querying and reasoning on a large frame-based knowledge graph. We also describe Word Frame Disambiguation, an application that reuses Framester data as a base in order to perform frame detection from text, with results comparable in precision to the state of the art, but with a much higher coverage.

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previous chapter On Emerging Entity Detection
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Footnotes
8
Many frames are not really wrong, but they are evoked as metaphorical or metonymical interpretations, e.g. the frame Travelling in a sentence like Our love traveled distances.
 
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Metadata
Title
Framester: A Wide Coverage Linguistic Linked Data Hub
Authors
Aldo Gangemi
Mehwish Alam
Luigi Asprino
Valentina Presutti
Diego Reforgiato Recupero
Copyright Year
2016
Book
Knowledge Engineering and Knowledge Management

Print ISBN: 978-3-319-49003-8

Electronic ISBN: 978-3-319-49004-5

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-49004-5_16

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