Authors:
Juana Maria Ruiz-Martinez
1
;
Rafael Valencia-García
1
;
Rodrigo Martínez-Béjar
1
and
Achim Hoffmann
2
Affiliations:
1
University of Murcia, Spain
;
2
University of New South Wales, Australia
Keyword(s):
Ontology Population, Semantic Role, Knowledge Acquisition.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Collaboration and e-Services
;
Data Engineering
;
e-Business
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Acquisition
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Natural Language Processing
;
Ontologies and the Semantic Web
;
Ontology Engineering
;
Pattern Recognition
;
Semantic Web
;
Soft Computing
;
Symbolic Systems
Abstract:
Ontology population is a knowledge acquisition activity that relies on (semi-) automatic methods to transform unstructured, semi-structured and structured data sources into instance data. In this work, a semantic-role based process for ontology population is presented that provides a suitable framework for textual knowledge acquisition in the biological domain. In particular, with our approach, a given ontology can be enriched by adding instances gathered from biological natural language texts. Our system’s modular architecture provides a greater versatility than current approaches in the mentioned domain, as the process of ontology population is not directly dependent on the linguistic rules developed from the corpus.