This paper describes the OAQA system evaluated in the BioASQ 4B Question Answering track. The system extends the Yang et al. (2015) system and integrates additional biomedical and generalpurpose NLP annotators, machine learning modules for search result scoring, collective answer reranking, and yes/no answer prediction. We first present the overall architecture of the system, and then focus on describing the main extensions to the Yang et al. (2015) approach. Before the official evaluation, we used the development dataset (excluding the 3B Batch 5 subset) for training. We present initial evaluation results on a subset of the development data set to demonstrate the effectiveness of the proposed new methods, and focus on performance analysis of yes/no question answering.
REF have described the OAQA system in BioASQ 4b based on NLP annotators, machine learning algorithms for search result scoring, collective answer re-ranking, and yes/no answer prediction.
Learning to Answer Biomedical Questions: OAQA at BioASQ 4B
Proceedings of the Fourth BioASQ workshop
Proceedings of the Fourth BioASQ workshop
Computer Science