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Erschienen in:
An Empirical Evaluation of RDF Graph Partitioning Techniques Kapitel lesen Erstes Kapitel lesen

2018 | OriginalPaper | Buchkapitel

Towards Enriching DBpedia from Vertical Enumerative Structures Using a Distant Learning Approach

verfasst von : Mouna Kamel, Cassia Trojahn

Erschienen in: Knowledge Engineering and Knowledge Management

Verlag: Springer International Publishing

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Abstract

Automatic construction of semantic resources at large scale usually relies on general purpose corpora as Wikipedia. This resource, by nature rich in encyclopedic knowledge, exposes part of this knowledge with strongly structured elements (infoboxes, categories, etc.). Several extractors have targeted these structures in order to enrich or to populate semantic resources as DBpedia, YAGO or BabelNet. The remain semi-structured textual structures, such as vertical enumerative structures (those using typographic and dispositional layout) have been however under-exploited. However, frequent in corpora, they are rich sources of specific semantic relations, such as hypernyms. This paper presents a distant learning approach for extracting hypernym relations from vertical enumerative structures of Wikipedia, with the aim of enriching DBpedia. Our relation extraction approach achieves an overall precision of 62%, and 99% of the extracted relations can enrich DBpedia, with respect to a reference corpus.

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Vorheriges Kapitel Making Sense of Numerical Data - Semantic Labelling of Web Tables
Nächstes Kapitel The Utility of the Abstract Relational Model and Attribute Paths in SQL
Fußnoten
1
A hypernym relation link two entities \(E_1\) and \(E_2\) when \(E_2\) (hyponym) is subordinate to \(E_1\) (hypernym). From a lexical point of view, this relation is called “isa”.
 
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Metadaten
Titel
Towards Enriching DBpedia from Vertical Enumerative Structures Using a Distant Learning Approach
verfasst von
Mouna Kamel
Cassia Trojahn
Copyright-Jahr
2018
Buch
Knowledge Engineering and Knowledge Management

Print ISBN: 978-3-030-03666-9

Electronic ISBN: 978-3-030-03667-6

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-3-030-03667-6_12