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The WebQuestions dataset is a question answering dataset using Freebase as the knowledge base and contains 6,642 question-answer pairs. It was created by crawling questions through the Google Suggest API, and then obtaining answers using Amazon Mechanical Turk. The original split uses 3,778 examples for training and 2,032 for testing. All answers are defined as Freebase entities. Example questions (answers) in the dataset include “Where did Edgar Allan Poe died?” (baltimore) or “What degrees did Barack Obama get?” (bachelor_of_arts, juris_doctor). Source: Question Answering with Subgraph Embeddings Image Source: Berant et al

ComplexWebQuestions is a dataset for answering complex questions that require reasoning over multiple web snippets. It contains a large set of complex questions in natural language, and can be used in multiple ways: 1. By interacting with a search engine; 2. As a reading comprehension task: the authors release 12,725,989 web snippets that are relevant for the questions, and were collected during the development of their model; 3. As a semantic parsing task: each question is paired with a SPARQL query that can be executed against Freebase to retrieve the answer. Source: Allen Institute for AI Image Source: Talmor et al

The WebQuestionsSP dataset is released as part of our ACL-2016 paper “The Value of Semantic Parse Labeling for Knowledge Base Question Answering” [Yih, Richardson, Meek, Chang & Suh, 2016], in which we evaluated the value of gathering semantic parses, vs. answers, for a set of questions that originally comes from WebQuestions [Berant et al., 2013]. The WebQuestionsSP dataset contains full semantic parses in SPARQL queries for 4,737 questions, and “partial” annotations for the remaining 1,073 questions for which a valid parse could not be formulated or where the question itself is bad or needs a descriptive answer. This release also includes an evaluation script and the output of the STAGG semantic parsing system when trained using the full semantic parses. More detail can be found in the document and labeling instructions included in this release, as well as the paper. Source: WebQuestions Semantic Parses Dataset