Abstract
Most of the information is available in the form of unstructured textual documents due to the growth of information sources (the Web for example). In this respect, to extract a set of events from texts written in natural language in the management change event, we have been introduced an open information extraction (OIE) system. For instance, in the management change event, a PERSON might be either the new coming person to the company or the leaving one. As a result, the Adaptive CRF approach (A-CRF) [15] has shown good performance results. However, it requires a lot of expert intervention during the construction of classifiers, which is time consuming. To palpate such a downside, we introduce an approach that reduces the expert intervention during the relation extraction. The named entity recognition and the reasoning which are automatic and based on techniques of adaptation and correspondence. Carried out experiments show the encouraging results of the main approaches of the literature.
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Notes
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The OLLIE tool is available at this address: https://github.com/knowitall/ollie.
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Acknowledgment
This work was made possible thanks to the Astra funding program Grant 2014-2020.4.01.16-032.
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Sahnoun, S., Elloumi, S., Yahia, S.B. (2019). Event Detection Based on Open Information Extraction and Ontology. In: Nguyen, N., Chbeir, R., Exposito, E., Aniorté, P., Trawiński, B. (eds) Computational Collective Intelligence. ICCCI 2019. Lecture Notes in Computer Science(), vol 11683. Springer, Cham. https://doi.org/10.1007/978-3-030-28377-3_20
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