Seminar: Extracting Ontological Knowledge from Textual Descriptions

Post date: Sep 18, 2017 12:1:25 PM

Speaker: Kevin Alex Mathews (CS14S030)

Date: 18th September, 2017 (Monday)

Time: 01:30 PM

Venue: Alan M Turing Hall (BSB 361),

Department of Computer Science and Engineering

Title: Extracting Ontological Knowledge from Textual Descriptions

Abstract: Authoring of OWL-DL ontologies is intellectually challenging and to make this process simpler, many systems accept natural language text as input. A text-based ontology authoring approach can be successful only when it is combined with an effective method for extracting ontological axioms from text. Extracting axioms from unrestricted English input is a substantially challenging task due to the richness of the language. Controlled natural languages (CNLs) have been proposed in this context and these tend to be highly restrictive. We propose a new CNL called TEDEI (TExtual DEscription Identifier) whose grammar is inspired by the different ways OWL-DL constructs are expressed in English. We built a system that transforms TEDEI sentences into corresponding OWL-DL axioms. Now, ambiguity due to different possible lexicalizations of sentences and semantic ambiguity present in sentences are challenges in this context. We find that the best way to handle these challenges is to construct axioms corresponding to alternative formalizations of the sentence so that the end-user can make an appropriate choice. The output is compared against human-authored axioms and in substantial number of cases, human-authored axiom is indeed one of the alternatives given by the system. The proposed system substantially enhances the types of sentence structures that can be used for ontology authoring.