Linguistically light lexical extensions for ontologies

Abstract

An increasing number of enterprises are beginning to include semantic web ontologies into their Information Extraction (IE) and Text Analytics (TA) applications. This can be challenging for a TA group wishing to avail of semantic web ontologies due to the manual effort of retargeting and tailoring language resources within the TA system to a new domain to meet customer needs. A lightweight lexical layer within an ontology offers a solution to this problem. Furthermore, the identification of class instances within unstructured text for either the purposes of ontology population or semantic annotation are usually limited to term mentions of proper noun, personal noun or fixed key phrases within Text Analytics or Ontology Based Information Extraction (OBIE) applications. These systems do not generalise to cope with compound nominal classes of multi word expressions. Leon, a set of Lexical Extensions for Ontologies offers a solution to this problem. We describe Leon, which encodes light linguistic features of lexical entries for concepts within an ontology, as well as a lightweight lexical analyzer which complies the Leon metadata into efficient an dictionary format to drive large scale identification and semantic annotation of concepts mentioned in text.