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: This paper used the real-time method to randomly collect 10% of publicly available English tweets using several pre-defined DDEO-related queries (Table TABREF6 ) within a specific time frame.  
 Question: Do they evaluate only on English data?
Example Output: Yes

Example Input: As in the Sequicity framework, we report entity match rate, BLEU score and Success F1 score.  
 Question: What were the evaluation metrics used?
Example Output: entity match rate BLEU score Success F1 score

Example Input: We provide three simple baselines for the RUN task: (1) NO-MOVE: the only position considered is the starting point; (2) RANDOM: As in BIBREF4, turn to a randomly selected heading, then execute a number of *WALK actions of an average route; (3) JUMP: at each sentence, extract entities from the map and move between them in the order they appear.  
 Question: What is the baseline?
Example Output:
NO-MOVE RANDOM JUMP