CSReader at SemEval-2018 Task 11: Multiple Choice Question Answering as Textual Entailment

Zhengping Jiang, Qi Sun
2018 Proceedings of The 12th International Workshop on Semantic Evaluation  
In this document we present an end-to-end machine reading comprehension system that solves multiple choice questions with a textual entailment perspective. Since some of the knowledge required is not explicitly mentioned in the text, we try to exploit common sense knowledge by using pretrained word embeddings during contextual embeddings and by dynamically generating a weighted representation of related script knowledge. In the model two kinds of prediction structure are ensembled, and the
more » ... accuracy of our system is 10 percent higher than the naiive baseline.
doi:10.18653/v1/s18-1176 dblp:conf/semeval/JiangS18 fatcat:p4h76e7osvdvfg5riz4lwa6uw4