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.

Ex Input:
As we can see that, all variants of our CRU model could give substantial improvements over the traditional GRU model, where a maximum gain of 2.7%, 1.0%, and 1.9% can be observed in three datasets, respectively.
Question: Do experiment results show consistent significant improvement of new approach over traditional CNN and RNN models?

Ex Output:
Yes

Ex Input:
First, we adapt a dataset extracted from Freebase, i.e., FB24K, which used by BIBREF26. Then, we collect extra entities and relations that from DBpedia which that they should have at least 100 mentions BIBREF7 and they could link to the entities in the FB24K by the sameAs triples. Finally, we build a datasets named as DBP24K. In addition, we build a game datasets from our game knowledge graph, named as Game30K.
Question: What three datasets are used to measure performance?

Ex Output:
FB24K DBP24K Game30K

Ex Input:
Here a small portion of the large parallel corpus for English-German is used as a simulation for the scenario where we do not have much parallel data: Translating texts in English to German.
Question: Which languages do they test on for the under-resourced scenario?

Ex Output:
English German