Developing and Evaluating a Context Dataset for How-to Tip Machine Reading Comprehension

Abstract

In this paper, we focus on the task of how-to tip machine reading comprehension (MRC), which is in the field of non-factoid MRC. Then, in the field of how-to tip MRC, we propose a method to build a context dataset, to which we apply a certain procedure of retrieving candidates of context paragraphs that are supposed to include candidates of answers to the given question. The information source of the context dataset is the column pages collected from how-to tip Web sites. We show that it is easy to develop a context dataset consisting of more than a few thousand context paragraphs. Then, we propose a procedure to combine a search module based on TF-IDF and a BERT machine reading comprehension model that is evaluated based on the context dataset developed in this paper.