Abstract
This 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.- Anthology ID:
- W17-0912
- Volume:
- Proceedings of the 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-level Semantics
- Month:
- April
- Year:
- 2017
- Address:
- Valencia, Spain
- Editors:
- Michael Roth, Nasrin Mostafazadeh, Nathanael Chambers, Annie Louis
- Venue:
- LSDSem
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 81–86
- Language:
- URL:
- https://aclanthology.org/W17-0912
- DOI:
- 10.18653/v1/W17-0912
- Cite (ACL):
- Pranav Goel and Anil Kumar Singh. 2017. IIT (BHU): System Description for LSDSem’17 Shared Task. In Proceedings of the 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-level Semantics, pages 81–86, Valencia, Spain. Association for Computational Linguistics.
- Cite (Informal):
- IIT (BHU): System Description for LSDSem’17 Shared Task (Goel & Singh, LSDSem 2017)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/W17-0912.pdf
- Data
- ROCStories