I wanted to train a chat bot for answering questions from books. I am trying to use Dynamic Memory Networks to do so.
- How can I generate a data set like facebook did in case of babi tasks so that it can tackle a variety of questions on the data set.
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If you are talking about "generating" in the sense of generative models , it is pretty tough. since we are still far beyond understanding the actual structure of question-answering.
And even state of the art methods for question answering are also not able to score well on datasets like babi , mostly 16 out of 20 tasks can be solved.
answered Jun 5 '18 at 15:42
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$\begingroup$ Thanks a lot for answering @thecomplexitytheorist. I wanted to create BaBI like tasks from a custom dataset - like a book. So it was not exactly like fully generating from scratch. $\endgroup$ – Shubham Bhardwaj Nov 2 '18 at 8:15
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This repository maintained by Facebook AI Research talks about how they went about generating QA from stories.
In essence, they try to simulate how a reader reads a story. They also keep track about the knowledge the reader is assimilating when reading. Then they frame a question based on the knowledge assimilated, in order to asses if the reader can perform logical inference given what knowledge is present with him.
