Answers.Body: <p><a href="https://github.com/facebook/bAbI-tasks#id17" rel="nofollow noreferrer">This</a> repository maintained by Facebook AI Research talks about how they went about generating QA from stories. </p>
  
  <p>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.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2018-11-02T08:25:16.393Z
Answers.LastActivityDate: 2018-11-02T08:25:16.393Z
Answers.UserDisplayName: Shubham Bhardwaj
Answers.Body: <p>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.</p>
  
  <p>And even state of the art methods for question answering are also not able to score well on datasets like <a href="http://classif.ai/dataset/babi/" rel="nofollow noreferrer">babi</a> , mostly 16 out of 20 tasks can be solved.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2018-11-02T08:15:20.963Z
Answers.Text: 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.
Answers.UserDisplayName: Shubham Bhardwaj
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2018-06-05T15:42:17.380Z
Answers.LastActivityDate: 2018-10-03T19:23:13.767Z
Answers.LastEditDate: 2018-10-03T19:23:13.767Z
Answers.UserDisplayName: thecomplexitytheorist
Body: <p>I wanted to train a chatbot for answering questions from books. I am trying to use <a href="https://arxiv.org/abs/1506.07285" rel="nofollow noreferrer">Dynamic Memory Networks</a> to do so.</p>
  <p>How can I generate a data set, as Facebook did in the case of <a href="https://research.fb.com/downloads/babi/" rel="nofollow noreferrer">bAbI tasks</a>, so that it can tackle a variety of questions on the data set?</p>
  
Tags: <natural-language-processing><training><datasets><chat-bots><question-answering>
Title: How to generate a dataset for question answering from books (like Facebook's bAbI)?
UserDisplayName: Shubham Bhardwaj
ThreadText: # How to generate a dataset for question answering from books (like Facebook's bAbI)?
  
  (Asked by: username_0 on 2017-06-05)
  
  I wanted to train a chatbot for answering questions from books. I am trying to use [Dynamic Memory Networks](https://arxiv.org/abs/1506.07285) to do so.
  
  How can I generate a data set, as Facebook did in the case of [bAbI tasks](https://research.fb.com/downloads/babi/), so that it can tackle a variety of questions on the data set?
  
  **Tags:** natural-language-processing, training, datasets, chat-bots, question-answering
  
  ---
  
  ## 2 answers
  
  ### Answer by username_0 on 2018-11-02. Score: 1 | Accepted answer
  
  [This](https://github.com/facebook/bAbI-tasks#id17) 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.
  
  
  ---
  
  ### Answer by username_1 on 2018-06-05. Score: 2
  
  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](http://classif.ai/dataset/babi/) , mostly 16 out of 20 tasks can be solved.
  
  > **Comments:**
  > **username_0**: 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.  
  
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