PhotoshopQuiA: A Corpus of Non-Factoid Questions and Answers for Why-Question Answering
Andrei Dulceanu, Thang Le Dinh, Walter Hong‐Shong Chang, Trung Bui, Doo Soon Kim, Manh Chiên Vu, Seokhwan Kim · 2018
Recent years have witnessed a high interest in non-factoid question answering using Community Question Answering (CQA) web sites.Despite ongoing research using state-of-the-art methods, there is a scarcity of available datasets for this task.Why-questions, which play an important role in open-domain and domain-specific applications, are difficult to answer automatically since the answers need to be constructed based on different information extracted from multiple knowledge sources.We introduce the PhotoshopQuiA dataset, a new publicly available set of 2,854 why-question and answer(s) (WhyQ, A) pairs related to Adobe Photoshop usage collected from five CQA web sites.We chose Adobe Photoshop because it is a popular and well-known product, with a lively, knowledgeable and sizable community.To the best of our knowledge, this is the first English dataset for Why-QA that focuses on a product, as opposed to previous open-domain datasets.The corpus is stored in JSON format and contains detailed data about questions and questioners as well as answers and answerers.The dataset can be used to build Why-QA systems, to evaluate current approaches for answering why-questions, and to develop new models for future QA systems research.