1. A knowledge representation system, comprising: a data store having a knowledge base stored therein comprising first knowledge represented in a structured, machine-readable format which encodes meaning and is distinct from natural language, the structured, machine-readable format primarily comprising assertions of named relationships between pairs of named entities; and at least one computing device operable to: add second knowledge in the structured, machine-readable format to the knowledge base, the second knowledge being generated with reference to input from a plurality of untrained, general internet users which is not in the structured, machine-readable format, at least some of the input from the users being in a particular natural language, wherein generating the second knowledge includes translating the input from the users to factual assertions compatible with the structured, machine-readable format using a plurality of translation templates, each of the translation templates including a respective predetermined pattern for matching against one or more natural language strings included in the input from the users, and wherein adding the second knowledge to the knowledge base includes determining whether the second knowledge is semantically contradicted by the first knowledge to promote consistency of the first and second knowledge across the knowledge base; generate third knowledge not represented in the knowledge base by inferring the third knowledge from one or more of the first knowledge or the second knowledge; and respond to queries using one or more of the first knowledge, the second knowledge, or the third knowledge.
1. A knowledge representation system, comprising: a data store having a knowledge base stored therein comprising first knowledge represented in a structured, machine-readable format which encodes meaning and is distinct from natural language, the structured, machine-readable format primarily comprising assertions of named relationships between pairs of named entities; and at least one computing device operable to: add second knowledge in the structured, machine-readable format to the knowledge base, the second knowledge being generated with reference to input from a plurality of untrained, general internet users which is not in the structured, machine-readable format, at least some of the input from the users being in a particular natural language, wherein generating the second knowledge includes translating the input from the users to factual assertions compatible with the structured, machine-readable format using a plurality of translation templates, each of the translation templates including a respective predetermined pattern for matching against one or more natural language strings included in the input from the users, and wherein adding the second knowledge to the knowledge base includes determining whether the second knowledge is semantically contradicted by the first knowledge to promote consistency of the first and second knowledge across the knowledge base; generate third knowledge not represented in the knowledge base by inferring the third knowledge from one or more of the first knowledge or the second knowledge; and respond to queries using one or more of the first knowledge, the second knowledge, or the third knowledge. 3. The system of claim 1 wherein the at least one computing device is operable to add the third knowledge to the knowledge base by capturing responses from a first one of the users to a sequence of natural language questions, aggregating the responses, and translating the aggregated responses to the structured, machine-readable format.