Question Answering for Machine Reading with Lexical Chain

Question answering for machine reading (QA4MR) is a task to understand the meaning communicated by a text. In this paper, we present our system in QA4MRE. The system follows the steps of reading comprehension as a language learner. Lexical chain is used to estimate the semantic relation between texts. Natural language processing (NLP) techniques are also widely used, such as: POS tagging, name entity recognition, coreference. On the QA4MRE test dataset, our system achieves the c@1 measure of 0.28 and 0.26 for the two submissions, respectively.