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Web search is an essential way for humans to obtain information, but it'sstill a great challenge for machines to understand the contents of web pages.In this paper, we introduce the task of structural reading comprehension (SRC)on web. Given a web page and a question about it, the task is to find theanswer from the web page. This task requires a system not only to understandthe semantics of texts but also the structure of the web page. Moreover, weproposed WebSRC, a novel Web-based Structural Reading Comprehension dataset.WebSRC consists of 400K question-answer pairs, which are collected from 6.4Kweb pages. Along with the QA pairs, corresponding HTML source code,screenshots, and metadata are also provided in our dataset. Each question inWebSRC requires a certain structural understanding of a web page to answer, andthe answer is either a text span on the web page or yes/no. We evaluate variousbaselines on our dataset to show the difficulty of our task. We alsoinvestigate the usefulness of structural information and visual features. Ourdataset and baselines have been publicly available athttps://x-lance.github.io/WebSRC/.

WebSRC: A Dataset for Web-Based Structural Reading Comprehension