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.

Q: To assess the consistency of annotations and also eliminate coincidental annotations, we used agreement rates, which is calculated by dividing the number of senses under each category where the annotators annotate consistently by the total number of each kind of sense. And considering the potential impact of unbalanced distribution of senses, we also used the Kappa value. 
 Question: Which inter-annotator metric do they use?

A: agreement rates Kappa value
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Q: Our study focused primarily on English tweets, since this was the language of our diagnostic training sample. 
 Question: Do the authors report results only on English datasets?

A: Yes
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Q: Our resulting model obtains state of the art results on both the VQA dataset and the bAbI-10k text question-answering dataset, proving the framework can be generalized across input domains. 
 Question: Does the DMN+ model establish state-of-the-art ?

A:
Yes
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