Question Answering (QA) is increasingly used by search engines to provide results to their end-users, yet very few websites currently use QA technologies for their search functionality. To illustrate the potential of QA technologies for the website search practitioner, we demonstrate web searches that combine QA over knowledge graphs and QA over free text -- each being usually tackled separately. We also discuss the different benefits and drawbacks of both approaches for web site searches. We use the case studies made of websites hosted by the Wikimedia Foundation (namely Wikipedia and Wikidata). Differently from a search engine (e.g. Google, Bing, etc), the data are indexed integrally, i.e. we do not index only a subset, and they are indexed exclusively, i.e. we index only data available on the corresponding website.

翻译：问答系统正日益被搜索引擎用于为终端用户提供结果，然而目前很少有网站在其搜索功能中应用问答技术。为向网站搜索从业者展示问答技术的潜力，我们演示了一种结合知识图谱问答与自由文本问答的网络搜索方法——这两种方法通常各自独立处理。我们还讨论了两种方法在网站搜索中的不同优势与局限性。本文以维基媒体基金会旗下网站（即维基百科与维基数据）为案例展开研究。与搜索引擎（如谷歌、必应等）不同，我们采用全量索引方式——即不限于数据子集，且采用独有索引方式——即仅索引对应网站的可获取数据。