21. A method comprising: receiving a question into a Question Answering (QA) system; said QA system comparing said question to a corpus of data; said QA system generating hypotheses about relationships between linguistic and semantic entities of said question and said corpus of data; said QA system generating a plurality of candidate answers to said question using said hypotheses; said QA system evaluating sources of evidence used to generate said plurality of candidate answers to identify marginal evidence, said marginal evidence contributing only partially to a candidate answer; said QA system determining a confidence score for each of said plurality of candidate answers; determining a missing piece of knowledge, said missing piece of knowledge comprising information that would enable said QA system to further develop said confidence score; formulating a follow-on inquiry to obtain said missing piece of knowledge; outputting said follow-on inquiry to an external expert community source separate from said QA system to obtain responses to said follow-on inquiry; receiving from said external expert community source responses to said follow-on inquiry comprising said missing piece of knowledge; inputting said missing piece of knowledge into said QA system; and said QA system automatically developing additional logical rules and additional evidence for said QA system based on said obtained missing piece of information.
21. A method comprising: receiving a question into a Question Answering (QA) system; said QA system comparing said question to a corpus of data; said QA system generating hypotheses about relationships between linguistic and semantic entities of said question and said corpus of data; said QA system generating a plurality of candidate answers to said question using said hypotheses; said QA system evaluating sources of evidence used to generate said plurality of candidate answers to identify marginal evidence, said marginal evidence contributing only partially to a candidate answer; said QA system determining a confidence score for each of said plurality of candidate answers; determining a missing piece of knowledge, said missing piece of knowledge comprising information that would enable said QA system to further develop said confidence score; formulating a follow-on inquiry to obtain said missing piece of knowledge; outputting said follow-on inquiry to an external expert community source separate from said QA system to obtain responses to said follow-on inquiry; receiving from said external expert community source responses to said follow-on inquiry comprising said missing piece of knowledge; inputting said missing piece of knowledge into said QA system; and said QA system automatically developing additional logical rules and additional evidence for said QA system based on said obtained missing piece of information. 23. The method of claim 21 , said QA system further comprising a plurality of passages, said method further comprising comparing said question to said plurality of passages to provide said plurality of candidate answers to said question.