Header

UZH-Logo

Maintenance Infos

Exploiting language resources for semantic web annotations


Kaljurand, K; Rinaldi, Fabio; Dowdall, J; Hess, M (2004). Exploiting language resources for semantic web annotations. In: LREC-2004, Lisbon, Portugal, 2004, 815-818.

Abstract

A large portion of the useful information on the web is in the form of unstructured natural language documents. Currently such documents are understandable to humans but not to software agents. One of the goals of the Semantic Web activity is to enrich a considerable number of web documents with annotations, which will then allow new generation search engines and novel web services to access those documents in a more intelligent fashion than currently possible. Currently the most reliable method of providing such semantic markup is via manual annotation, possibly based on predefined ontologies and with the support of specialized editors. In this paper we propose an approach for the automatic processing of textual documents to be published on the web, which can be used to automatically
generate (some of) the semantic annotations. In particular, we focus on detecting the entities mentioned in the documents, their roles and relationships to other entities.

Abstract

A large portion of the useful information on the web is in the form of unstructured natural language documents. Currently such documents are understandable to humans but not to software agents. One of the goals of the Semantic Web activity is to enrich a considerable number of web documents with annotations, which will then allow new generation search engines and novel web services to access those documents in a more intelligent fashion than currently possible. Currently the most reliable method of providing such semantic markup is via manual annotation, possibly based on predefined ontologies and with the support of specialized editors. In this paper we propose an approach for the automatic processing of textual documents to be published on the web, which can be used to automatically
generate (some of) the semantic annotations. In particular, we focus on detecting the entities mentioned in the documents, their roles and relationships to other entities.

Statistics

Downloads

113 downloads since deposited on 10 Sep 2009
1 download since 12 months
Detailed statistics

Additional indexing

Item Type:Conference or Workshop Item (Paper), refereed, original work
Communities & Collections:06 Faculty of Arts > Institute of Computational Linguistics
Dewey Decimal Classification:000 Computer science, knowledge & systems
410 Linguistics
Scopus Subject Areas:Social Sciences & Humanities > Library and Information Sciences
Social Sciences & Humanities > Education
Social Sciences & Humanities > Language and Linguistics
Social Sciences & Humanities > Linguistics and Language
Language:English
Event End Date:2004
Deposited On:10 Sep 2009 13:03
Last Modified:05 Mar 2022 08:14
OA Status:Green