In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.

Input: Consider Input: In order to derive the discourse features, an entity grid is constructed by feeding the document through an NLP pipeline to identify salient entities. Two flavors of discourse features are created by populating the entity grid with either (i) grammatical relations (GR) or (ii) RST discourse relations (RST).
Question: What discourse features are used?

Output: Entity grid with grammatical relations and RST discourse relations.

Input: Consider Input: Hence, the continuous relaxation to top-k-argmax operation can be simply implemented by iteratively using the max operation which is continuous and allows for gradient flow during backpropagation.
Question: Which loss metrics do they try in their new training procedure evaluated on the output of beam search?

Output: continuous relaxation to top-k-argmax

Input: Consider Input: We validate our approach on the Wikipedia toxic comments dataset BIBREF18 .
Question: Which datasets do they use?
Output: Wikipedia toxic comments