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: 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?

Output: agreement rates Kappa value

Input: Consider Input: In this work, we develop a technique to rapidly transfer an existing pre-trained model from English to other languages in an energy efficient way BIBREF8.
Question: How much training data from the non-English language is used by the system?

Output: No data. Pretrained model is used.

Input: Consider Input: The NLG model is a seq2seq model with attention as described in section SECREF2.
Question: Do they use attention?
Output: Yes