Improving Open Information Extraction for Semantic Web Tasks

Authors: Cheikh, Kacfah Emani; Catarina, Ferreira Da Silva;Bruno, Fiès;Parisa, Ghodous
Year: 2015
Venue:
Link: http://link.springer.com/chapter/10.1007/978-3-662-49521-6_6
Product of the Action: No

Abstract:
Open Information Extraction (OIE) aims to automatically identify all the possible assertions within a sentence. Results of this task are usually a set of triples (subject, predicate, object). In this paper, we first present what OIE is and how it can be improved when we work in a given domain of knowledge. Using a corpus made up of sentences in building engineering construction, we obtain an improvement of more than 18 %. Next, we show how OIE can be used at a base of a high-level semantic web task. Here we have applied OIE on formalisation of natural language definitions. We test this formalisation task on a corpus of sentences defining concepts found in the pizza ontology. At this stage, 70.27 % of our 37 sentences-corpus are fully rewritten in OWL DL.