In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.
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Question: The resulting set of 46 documents makes up our base corpus. Note that these documents vary greatly in size, which means the resulting corpus is varied, but not balanced in terms of size (Table TABREF43).

Answer: How big PIE datasets are obtained from dictionaries?


Question: For testing, we also applied the TongueNet on the UBC database BIBREF14 without any training to see the generalization ability of the model.

Answer: What previously annotated databases are available?


Question: The final results for our F1-score from this classification technique are 0.52 and 0.31 for the single and multi-turn data respectively.

We compare our results for both the single-turn and multi-turn experiments to the accuracies on the test data based off the BLEU score.

Answer:
which existing metrics do they compare with?