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:  To evaluate real-world performance of our selected classifier (i.e., performance in the absence of model and parameter bias), we perform classification of the holdout set. On this set, our classifier had an accuracy and F1-score of 89.6% and 89.2%, respectively.  
 Question: What was their system's performance?

A: accuracy and F1-score of 89.6% and 89.2%, respectively
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Q: We first conduct experiments to compare the performance of FlowSeq with strong baseline models, including NAT w/ Fertility BIBREF6, NAT-IR BIBREF7, NAT-REG BIBREF25, LV NAR BIBREF26, CTC Loss BIBREF27, and CMLM BIBREF8. 
 Question: What non autoregressive NMT models are used for comparison?

A: NAT w/ Fertility NAT-IR NAT-REG LV NAR CTC Loss CMLM
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Q: The competition is divided into five subtasks which involve standard classification, ordinal classification and distributional estimation. For a more detailed description see BIBREF0 . 
 Question: What were the five English subtasks?

A:
 five subtasks which involve standard classification, ordinal classification and distributional estimation. For a more detailed description see BIBREF0
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