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:
All documents are segmented into paragraphs and processed at the paragraph level (both training and inference); this is acceptable because we observe that most paragraphs are less than 200 characters. The input sequences are segmented by the BERT tokenizer, with the special [CLS] token inserted at the beginning and the special [SEP] token added at the end. 
 Question: At what text unit/level were documents processed?
answer:
documents are segmented into paragraphs and processed at the paragraph level


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:
Argus Dataset AI2-8grade/CK12 Dataset We consider this dataset as preliminary since it was not reviewed by a human and many hypotheses are apparently unprovable by the evidence we have gathered (i.e. the theoretical top accuracy is much lower than 1.0).  MCTest Dataset We use an official extension of the dataset for RTE evaluation that again textually merges questions and answers. 
 Question: what datasets did they use?
answer:

Argus Dataset AI2-8grade/CK12 Dataset MCTest Dataset