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.

Example Input: The annotator carried out all annotation.
Question: How many annotators tagged each tweet?
Example Output: One

Example Input: We evaluate our method on IWSLT16 German-English (DE-EN) translation in both directions, WMT15 English-German (EN-DE) translation in both directions, and NIST Chinese-to-English (ZH$
ightarrow $EN) translation.
Question: Which languages do they experiment on?
Example Output: German English Chinese

Example Input: Further, FSDM has a new module called response slot binary classifier that adds extra supervision to generate the slots that will be present in the response more precisely before generating the final textual agent response (see Section "Methodology" for details).
Question: How do slot binary classifiers improve performance?
Example Output:
by adding extra supervision to generate the slots that will be present in the response