Abstract
This paper describes our participation in SemEval-2017 Task 3 on Community Question Answering (cQA). The Question Similarity subtask (B) aims to rank a set of related questions retrieved by a search engine according to their similarity to the original question. We adapted our feature-based system for Recognizing Question Entailment (RQE) to the question similarity task. Tested on cQA-B-2016 test data, our RQE system outperformed the best system of the 2016 challenge in all measures with 77.47 MAP and 80.57 Accuracy. On cQA-B-2017 test data, performances of all systems dropped by around 30 points. Our primary system obtained 44.62 MAP, 67.27 Accuracy and 47.25 F1 score. The cQA-B-2017 best system achieved 47.22 MAP and 42.37 F1 score. Our system is ranked sixth in terms of MAP and third in terms of F1 out of 13 participating teams.- Anthology ID:
- S17-2057
- Volume:
- Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
- Month:
- August
- Year:
- 2017
- Address:
- Vancouver, Canada
- Venue:
- SemEval
- SIG:
- SIGLEX
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 349–352
- Language:
- URL:
- https://aclanthology.org/S17-2057
- DOI:
- 10.18653/v1/S17-2057
- Cite (ACL):
- Asma Ben Abacha and Dina Demner-Fushman. 2017. NLM_NIH at SemEval-2017 Task 3: from Question Entailment to Question Similarity for Community Question Answering. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), pages 349–352, Vancouver, Canada. Association for Computational Linguistics.
- Cite (Informal):
- NLM_NIH at SemEval-2017 Task 3: from Question Entailment to Question Similarity for Community Question Answering (Ben Abacha & Demner-Fushman, SemEval 2017)
- PDF:
- https://preview.aclanthology.org/paclic-22-ingestion/S17-2057.pdf