instruction:
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.
question:
after a shared CLWE space has been induced, the task is to retrieve target language translations for a test set of source language words retrieve target language translations for a test set of source language words BLI is cast as a ranking task in our BLI setup with only one correct translation for each “query” word, MAP is equal to mean reciprocal rank (MRR) 
 Question: How does BLI measure alignment quality?
answer:
we use mean average precision (MAP) as the main evaluation metric


question:
Encoders with induced latent structures have been shown to benefit several tasks including document classification, natural language inference BIBREF12, BIBREF13, and machine translation BIBREF11.  
 Question: Is there any evidence that encoders with latent structures work well on other tasks?
answer:
Yes


question:
For the competition, we provided 1,000 labeled dialogues from each dataset for training, and 240 unlabeled dialogues from each dataset for evaluation.  
 Question: What is the size of the second dataset?
answer:

1 000 labeled dialogues for training and 240 unlabeled dialogues for evaluation