Multiple-choice question answering based on textual entailment

This paper proposes a method to compute textual entailment strength, taking multiple-choice questions which have clear candidate answers as research objects, aiming at the phenomenon of long text entailing short text. Two methods are used to answer the college entrance examination geography multiple-choice questions based on the Wikipedia Chinese Corpus in the absence of large-scale questions and answers. One is based on the sentence similarity and the other is based on the textual entailment proposed above. The accuracy rate of the proposed method is 36.93%, increasing by 2.44% than the way based on the word embedding sentence similarity, increasing 7.66% than the way based on the Vector Space Model sentence similarity, which confirm the effectiveness of the method based on the textual entailment.