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
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To succeed the Future Internet will need to address a number of cross-cutting challenges including:
- Scalability in the face of peer-to-peer traffic, decentralisation, and increased openness
- Trust when government, medical, financial, personal data are increasingly trusted to the cloud, and middleware will increasingly use dynamic service selection
- Interoperability of semantic data and metadata, and of services which will be dynamically orchestrated
- Pervasive usability for users of mobile devices, different languages, cultures and physical abilities
- Mobility for users who expect a seamless experience across spaces, devices, and velocities
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