Tech Reports
Tech Report kmi-06-17 Abstract
Relation Extraction for Semantic Intranet Annotations
Techreport ID: kmi-06-17
Date: 2006
Author(s): Lucia Specia, Claudio Baldassarre, Enrico Motta
We present an approach for ontology driven extraction of relations from texts aimed mainly to produce enriched semantic annotations for the Semantic Web. The approach exploits linguistic and empirical strategies, by means of a pipeline method involving processes such as a parser, part-of-speech tagger, named entity recognition system, and pattern-based classification, and resources including ontology, knowledge and lexical databases. A preliminary evaluation with 25 sentences showed that the use of knowledge intensive resources and strategies together with corpus-based techniques to process the input data allows identifying and discovering relevant relations between known and new entity pairs mentioned in the text. Besides semantic web annotations, the system can be used for other tasks, including ontology population, since it identifies new instantiations of existent relations and entities, and ontology learning, since it discovers new relations, which are not part of the ontology.
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Semantic Web and Knowledge Services is...
Our research in the Semantic Web area looks at the potentials of fusing together advances in a range of disciplines, and applying them in a systemic way to simplify the development of intelligent, knowledge-based web services and to facilitate human access and use of knowledge available on the web. For instance, we are exploring ways in which tnatural language interfaces can be used to facilitate access to data distributed over different repositories. We are also developing infrastructures to support rapid development and deployment of semantic web services, which can be used to create web applications on-the-fly. We are also investigating ways in which semantic technology can support learning on the web, through a combination of knowledge representation support, pedagogical theories and intelligent content aggregation mechanisms. Finally, we are also investigating the Semantic Web itself as a domain of analysis and performing large scale empirical studies to uncover data about the concrete epistemologies which can be found on the Semantic Web. This exciting new area of research gives us concrete insights on the different conceptualizations that are present on the Semantic Web by giving us the possibility to discover which are the most common viewpoints, which viewpoints are mutually inconsistent, to what extent different models agree or disagree, etc...
Our aim is to be at the forefront of both theoretical and practical developments on the Semantic Web not only by developing theories and models, but also by building concrete applications, for a variety of domains and user communities, including KMi and the Open University itself.
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