The University of Southampton
University of Southampton Institutional Repository

Question Answering Towards Automatic Augmentations of Ontology Instances

Question Answering Towards Automatic Augmentations of Ontology Instances
Question Answering Towards Automatic Augmentations of Ontology Instances
Ontology instances are in general stored as triples which associate two related entities with pre-defined relational descriptions. Sometimes such triples can be incomplete in that one entity is known but the other entity is missing. The automatic acquisition of the missing values is closely related to relation extraction systems that extracts binary relations between two identified entities. Relation extraction systems rely on the availability of named entities in that mislabelled entities can decrease the number of relations correctly identified. Although recent results demonstrate over 80% accuracy for recognising named entities, when input texts have less consistent patterns, the performance decreases rapidly. This paper presents OntotripleQA which is the application of question-answering techniques to relation extraction in order to reduce the reliance on the named entities and take into account other assessments when evaluating potential relations. Not only does this increase the number of relations extracted, but it also improves the accuracy in extracting relations by considering features which are not extractable only by comparison with named entities. A small dataset was collected to test the proposed approach and the experiment demonstrates that it is effective on the sentences of the Web documents obtaining 68% performance on average.
relation extraction, ontology population, information extraction, question answering systems
3-540-21999-4
152-166
Kim, Sanghee
9e0e5909-9fbe-4c37-9606-2fdea35eac12
Lewis, Paul
7aa6c6d9-bc69-4e19-b2ac-a6e20558c020
Martinez, Kirk
5f711898-20fc-410e-a007-837d8c57cb18
Goodall, Simon
e436aca8-e9d8-4970-a2c1-d4c8129e976d
Kim, Sanghee
9e0e5909-9fbe-4c37-9606-2fdea35eac12
Lewis, Paul
7aa6c6d9-bc69-4e19-b2ac-a6e20558c020
Martinez, Kirk
5f711898-20fc-410e-a007-837d8c57cb18
Goodall, Simon
e436aca8-e9d8-4970-a2c1-d4c8129e976d

Kim, Sanghee, Lewis, Paul, Martinez, Kirk and Goodall, Simon (2004) Question Answering Towards Automatic Augmentations of Ontology Instances At The Semantic Web: Research and Applications: First European Semantic Web Symposium, ESWS, Greece. , pp. 152-166.

Record type: Conference or Workshop Item (Paper)

Abstract

Ontology instances are in general stored as triples which associate two related entities with pre-defined relational descriptions. Sometimes such triples can be incomplete in that one entity is known but the other entity is missing. The automatic acquisition of the missing values is closely related to relation extraction systems that extracts binary relations between two identified entities. Relation extraction systems rely on the availability of named entities in that mislabelled entities can decrease the number of relations correctly identified. Although recent results demonstrate over 80% accuracy for recognising named entities, when input texts have less consistent patterns, the performance decreases rapidly. This paper presents OntotripleQA which is the application of question-answering techniques to relation extraction in order to reduce the reliance on the named entities and take into account other assessments when evaluating potential relations. Not only does this increase the number of relations extracted, but it also improves the accuracy in extracting relations by considering features which are not extractable only by comparison with named entities. A small dataset was collected to test the proposed approach and the experiment demonstrates that it is effective on the sentences of the Web documents obtaining 68% performance on average.

Microsoft Word sangheekimesws2004-prepress.doc - Other
Download (410kB)

More information

Published date: 2004
Additional Information: Event Dates: May 2004
Venue - Dates: The Semantic Web: Research and Applications: First European Semantic Web Symposium, ESWS, Greece, 2004-05-01
Keywords: relation extraction, ontology population, information extraction, question answering systems
Organisations: Web & Internet Science

Identifiers

Local EPrints ID: 258911
URI: http://eprints.soton.ac.uk/id/eprint/258911
ISBN: 3-540-21999-4
PURE UUID: d9e8e2d9-8325-444f-a561-c6b89ab76269
ORCID for Kirk Martinez: ORCID iD orcid.org/0000-0003-3859-5700

Catalogue record

Date deposited: 02 Mar 2005
Last modified: 18 Jul 2017 09:29

Export record

Contributors

Author: Sanghee Kim
Author: Paul Lewis
Author: Kirk Martinez ORCID iD
Author: Simon Goodall

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×