If people are interested in playing with the dataset from &quot;Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks&quot;, I added an example to Keras that uses recurrent neural networks[1]. It achieves similar accuracy to the baseline LSTM approach in the paper. I also did a write-up that explains the task and architecture[2].<p>The dataset (bAbi tasks[3]) released by Facebook is interesting but has a number of limitations. The code used to produce it is also not open source. If someone has the interest and&#x2F;or past experience in MUD style environments, creating an open source dataset would be amazing!<p>[1]: <a href="https:&#x2F;&#x2F;github.com&#x2F;fchollet&#x2F;keras&#x2F;blob&#x2F;master&#x2F;examples&#x2F;babi_rnn.py" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;fchollet&#x2F;keras&#x2F;blob&#x2F;master&#x2F;examples&#x2F;babi_...</a><p>[2]: <a href="http:&#x2F;&#x2F;smerity.com&#x2F;articles&#x2F;2015&#x2F;keras_qa.html" rel="nofollow">http:&#x2F;&#x2F;smerity.com&#x2F;articles&#x2F;2015&#x2F;keras_qa.html</a><p>[3]: <a href="https:&#x2F;&#x2F;research.facebook.com&#x2F;researchers&#x2F;1543934539189348" rel="nofollow">https:&#x2F;&#x2F;research.facebook.com&#x2F;researchers&#x2F;1543934539189348</a>