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Is anyone aware of any machine learning question-answering frameworks? The only ones I'm currently aware of are Ephyra and Qanus, but they both seem like academic toys that haven't had much development and have since died. I couldn't even get Qanus to run, as it seems to have several dependencies that aren't terribly well documented.
Note, I'm not talking about OpenQA/StackOverflow-like social web QA frameworks, or proprietary black-box web services like Wolfram Alpha or True Knowledge.
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Open-Domain Question-Answering (QA) systems accept natural language questions as input and return exact answers from content buried within large text corpora such as Wikipedia. This is very different from standard search engines that simply return the documents that match keywords in a search query.
CLOSED DOMAIN QUESTION ANSWERING SYSTEM USING NLP TECHNIQUES Question Answering (QA) system in information retrieval is a task of automatically answering a correct answer to the questions asked by human in natural language using either a pre-structured database or a collection of natural language documents.
Have you also checked out Qanda? I think that the reason why most of these projects are dormant/abandoned is that the real difficulty for a question answering system does not really lie in algorithms and coding, but rather in building a knowledge corpus, which involves a lot of painstaking labor.
Also, results will tend to be much better if the system is domain-specific rather than general purpose, because you can tailor the corpus for a particular set of subjects.
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