Populating Biomedical Ontologies from Natural Language Texts.

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.