Improving open information extraction for semantic web tasks

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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 highlevel 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.

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Emani, C. K., da Silva, C. F., Fiès, B., & Ghodous, P. (2016). Improving open information extraction for semantic web tasks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9630, pp. 139–158). Springer Verlag. https://doi.org/10.1007/978-3-662-49521-6_6

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