7. The system as in claim 5 , wherein said determining a number of said entity structures having terms in said embedded tags or links that match query terms comprises: determining a similarity of a term in an embedded tag or said embedded link to another document and said query terms; and estimating a relevance of the candidate answer to the question based on the determined similarity.
5. A system for automatically scoring candidate answers to questions in a question and answer system comprising: a memory storage device; a processor device in communication with the memory device that performs a method comprising: receiving plural candidate answers associated with a query string, said plural candidate answers obtained from at least one document in a data corpus using query terms; identifying one or more entity structures embedded in said at least one document; and for each at least one document: extracting said one or more entity structures embedded in said at least one document, said embedded entity structures comprising user embedded tags or embedded links to other documents; determining a number of said entity structures having terms in said embedded tags or said embedded links to other documents that match query terms in the received input query string; computing a score for each of said plural candidate answers in said document as a function of a count of said number of entity structures having terms in said embedded tags or said embedded links to other documents that match query terms in the query string; said score computing comprising: assigning an associated weight to a count of said matching query terms associated with each said score for each said plural candidate answer; and computing a final score by combining each weighted match count associated with each of the candidate answers.