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:
  In a second step, we will train a neural monolingual translation system, that translates from the output of the PBMT system INLINEFORM0 to a better target sentence INLINEFORM1 . 
 Question: Do they train the NMT model on PBMT outputs?
answer:
Yes


question:
A recently published dataset called SCAN BIBREF2 (Simplified version of the CommAI Navigation tasks), tests compositional generalization in a sequence-to-sequence (seq2seq) setting by systematically holding out of the training set all inputs containing a basic primitive verb ("jump"), and testing on sequences containing that verb. 
 Question: How does the SCAN dataset evaluate compositional generalization?
answer:
it systematically holds out inputs in the training set containing basic primitive verb, "jump", and tests on sequences containing that verb.


question:
The BioNLP 2009 Shared Task BIBREF195 was based on the GENIA corpus BIBREF196 which contains PubMed abstracts of articles on transcription factors in human blood cells. 
 Question: Which datasets are used in this work?
answer:

GENIA corpus