In open-domain QA, many questions are concerned with properties of named entities, such as birth date, birth place, occupation, and other personal attributes of well-known present and historical individuals, locations, ownership, and products of various companies, facts about consumer products, geographical facts, and so on. For answering such questions, it makes sense to pre-assemble the relevant factoids into a large knowledge base, using knowledge acquisition methods like those in section 8. Examples of systems containing an abundance of factoids about named entities are several developed at the University of Washington, storing factoids as text fragments, and various systems that map harvested factoids into RDF (Resource Description Framework) triples  (see references in Other Internet Resources). Some of these systems obtain their knowledge not only from open information extraction and targeted relation extraction, but also from such sources as Wikipedia “infoboxes” and (controlled) crowdsourcing. Here we are also stretching the notion of question answering, since several of the mentioned systems require the use of key words or query patterns for retrieval of factoids.