IITP at MEDIQA 2019: Systems Report for Natural Language Inference, Question Entailment and Question Answering
Dibyanayan Bandyopadhyay, Baban Gain, Tanik Saikh, Asif Ekbal
Abstract
This paper presents the experiments accomplished as a part of our participation in the MEDIQA challenge, an (Abacha et al., 2019) shared task. We participated in all the three tasks defined in this particular shared task. The tasks are viz. i. Natural Language Inference (NLI) ii. Recognizing Question Entailment(RQE) and their application in medical Question Answering (QA). We submitted runs using multiple deep learning based systems (runs) for each of these three tasks. We submitted five system results in each of the NLI and RQE tasks, and four system results for the QA task. The systems yield encouraging results in all the three tasks. The highest performance obtained in NLI, RQE and QA tasks are 81.8%, 53.2%, and 71.7%, respectively.- Anthology ID:
- W19-5056
- Volume:
- Proceedings of the 18th BioNLP Workshop and Shared Task
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Dina Demner-Fushman, Kevin Bretonnel Cohen, Sophia Ananiadou, Junichi Tsujii
- Venue:
- BioNLP
- SIG:
- SIGBIOMED
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 517–522
- Language:
- URL:
- https://aclanthology.org/W19-5056
- DOI:
- 10.18653/v1/W19-5056
- Cite (ACL):
- Dibyanayan Bandyopadhyay, Baban Gain, Tanik Saikh, and Asif Ekbal. 2019. IITP at MEDIQA 2019: Systems Report for Natural Language Inference, Question Entailment and Question Answering. In Proceedings of the 18th BioNLP Workshop and Shared Task, pages 517–522, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- IITP at MEDIQA 2019: Systems Report for Natural Language Inference, Question Entailment and Question Answering (Bandyopadhyay et al., BioNLP 2019)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/W19-5056.pdf