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.

Q: We also run a manual evaluation which shows for the En-It task a slight quality degradation in exchange of a statistically significant reduction in the average length ratio, from 1.05 to 1.01. 
 Question: Do they conduct any human evaluation?

A: Yes
****
Q:  For the embeddings, we relied on $AraVec$ BIBREF30 for Arabic, FastText BIBREF31 for French, and Word2vec Google News BIBREF32 for English .  
 Question: What monolingual word representations are used?

A: AraVec for Arabic, FastText for French, and Word2vec Google News for English.
****
Q: We adopt the following two datasets:

Quora BIBREF1: The Quora Question Pairs dataset contains question pairs annotated with labels indicating whether the two questions are paraphrases. We use the same dataset partition as BIBREF5, with 384,348/10,000/10,000 pairs in the training/development/test set respectively.

MRPC BIBREF34: The Microsoft Research Paraphrase Corpus consists of sentence pairs collected from online news. Each pair is annotated with a label indicating whether the two sentences are semantically equivalent. There are 4,076/1,725 pairs in the training/test set respectively. 
 Question: What are benhmark datasets for paraphrase identification?

A:
Quora MRPC
****