AICLSep 25, 2017

Extracting Ontological Knowledge from Textual Descriptions

arXiv:1709.08448v38 citations
AI Analysis

This work addresses the problem of simplifying ontology creation for users by enabling more flexible sentence structures, though it is incremental as it builds on existing controlled natural language approaches.

The paper tackles the challenge of extracting ontological axioms from natural language text for OWL-DL ontology authoring by proposing a new controlled natural language called TEDEI, which transforms sentences into OWL-DL axioms and provides alternative formalizations, with the system's output matching human-authored axioms in many cases.

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. In this paper, 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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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