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IIT (BHU): System Description for LSDSem’17 Shared Task

dc.contributor.authorGoel P.; Singh A.K.
dc.date.accessioned2025-05-24T09:30:22Z
dc.description.abstractThis paper describes an ensemble system submitted as part of the LSDSem Shared Task 2017 - the Story Cloze Test. The main conclusion from our results is that an approach based on semantic similarity alone may not be enough for this task. We test various approaches and compare them with two ensemble systems. One is based on voting and the other on logistic regression based classifier. Our final system is able to outperform the previous state of the art for the Story Cloze test. Another very interesting observation is the performance of sentiment based approach which works almost as well on its own as our final ensemble system. © 2017 Association for Computational Linguistics
dc.identifier.doihttps://doi.org/10.18653/v1/w17-0912
dc.identifier.urihttp://172.23.0.11:4000/handle/123456789/16961
dc.relation.ispartofseriesLSDSem 2017 - 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-Level Semantics, Proceedings of the Workshop
dc.titleIIT (BHU): System Description for LSDSem’17 Shared Task

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