FAQ documents are commonly used with text documents and websites to provide
important information in the form of question answer pairs to either aid in
reading comprehension or provide a shortcut to the key ideas. We suppose that
salient sentences from a given document serve as a good proxy fro the answers
to an aggregated set of FAQs from readers. We propose a system for generating
FAQ documents that extract the salient questions and their corresponding
answers from sizeable text documents scraped from the Stanford Encyclopedia of
Philosophy. We use existing text summarization, sentence ranking via the Text
rank algorithm, and question-generation tools to create an initial set of
questions and answers. Finally, we apply some heuristics to filter out invalid
questions. We use human evaluation to rate the generated questions on grammar,
whether the question is meaningful, and whether the question's answerability is
present within a summarized context. On average, participants thought 71
percent of the questions were meaningful.

从 Stanford 哲学百科网站获取的大量文本文档中提取突出的问题和相应的答案，使用现有的文本摘要、文本排序和问题生成工具创建初始的问题和答案集合，通过人工评估得出平均参与者认为 71% 的问题具有意义。