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Please use this identifier to cite or link to this item: https://idr.l3.nitk.ac.in/jspui/handle/123456789/8677
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dc.contributor.authorBarathi, Ganesh, H.B.
dc.contributor.authorSoman, K.P.
dc.contributor.authorReshma, U.
dc.contributor.authorKale, M.
dc.contributor.authorMankame, P.
dc.contributor.authorKulkarni, G.
dc.contributor.authorKale, A.
dc.contributor.authorAnand, Kumar, M.
dc.date.accessioned2020-03-30T10:22:33Z-
dc.date.available2020-03-30T10:22:33Z-
dc.date.issued2018
dc.identifier.citationCEUR Workshop Proceedings, 2018, Vol.2266, , pp.119-128en_US
dc.identifier.urihttp://idr.nitk.ac.in/jspui/handle/123456789/8677-
dc.description.abstractThis overview paper describes the first shared task on Information Extractor for Conversational Systems in Indian Languages (IECSIL) which has been organized by FIRE 2018. Motivated by the need of Information Extractor, corpora has been developed to perform the Named Entity Recognition (Task A) and Relation Extraction (Task B) for five Indian languages (Hindi, Tamil, Malayalam, Telugu and Kannada). Task A is to identify and classify the named entities to one of the many classes and Task B is to extract the relation among the entities present in the sentences. Altogether, nearly 100 submission of 10 different teams were evaluated. In this paper, we have given an overview of the approaches and also discussed the results that the participated teams have attained. � 2018 CEUR-WS. All Rights Reserved.en_US
dc.titleOverview of Arnekt IECSIL at Fire-2018 track on information extraction for conversational systems in Indian languagesen_US
dc.typeBook chapteren_US
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