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.
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Question: Fig. FIGREF4 shows the distributions of seven question types grouped deterministically from the lexicons. 
 Question: How many question types do they find in the datasets analyzed?

Answer: seven 


Question: We optimized our single-task baseline to get a strong baseline in order to exclude better results in multi-task learning in comparison to single-task learning only because of these two following points: network parameters suit the multi-task learning approach better and a better randomness while training in the multi-task learning. To exclude the first point, we tested different hyperparameters for the single-task baseline. We tested all the combinations of the following hyperparameter values: 256, 512, or 1024 as the sizes for the hidden states of the LSTMs, 256, 512, or 1024 as word embedding sizes, and a dropout of 30 %, 40 %, or 50 %. We used subword units generated by byte-pair encoding (BPE) BIBREF16 as inputs for our model. To avoid bad subword generation for the synthetic datasets, in addition to the training dataset, we considered the validation and test dataset for the generating of the BPE merge operations list. We trained the configurations for 14 epochs and trained every configuration three times. We chose the training with the best quality with regard to the validation F1-score to exclude disadvantages of a bad randomness. We got the best quality with regard to the F1-score with 256 as the size of the hidden states of the LSTMs, 1024 as word embedding size, and a dropout of 30 %. For the batch size, we used 64. 
 Question: What are the strong baselines you have?

Answer: optimize single task with no synthetic data


Question: To test whether horizontal or vertical consistency is more helpful, we train and evaluate M-Bert on a dataset variant where all questions are in their English version. 
 Question: Did they pefrorm any cross-lingual vs single language evaluation?

Answer:
Yes