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: Fig. FIGREF4 shows the distributions of seven question types grouped deterministically from the lexicons.
Question: How many question types do they find in the datasets analyzed?

Output: seven

Input: Consider Input: For comparison purpose, we build two baseline systems for each direction: one is use the traditional phrase-based statistical machine translation (SMT), the other one is the NMT system.
Question: what was the baseline?

Output: traditional phrase-based statistical machine translation (SMT) NMT system

Input: Consider Input: In this way, an attention vector sequence is segmented into several subsequences and each subsequence represents the attention of one word. Then, motivated by the psycholinguistic finding that readers are likely to pay approximate attention to each character in one Chinese word, we devise an appropriate aggregation module to fuse the inner-word character attention.
Question: How does the fusion method work?
Output: ttention vector sequence is segmented into several subsequences and each subsequence represents the attention of one word we devise an appropriate aggregation module to fuse the inner-word character attention