instruction:
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.
question:
In particular, we investigated attention to nouns, verbs, pronouns, subjects, objects, and negation words, and special BERT tokens across the tasks.
answer:
What handcrafter features-of-interest are used?


question:
The model consists of one layer of LSTM followed by three dense layers. The LSTM layer uses a dropout value of 0.2. 
answer:
Do they use dropout?


question:
This step entails counting occurrences of all words in the training corpus and sorting them in order of decreasing occurrence. As mentioned, the vocabulary is taken to be the INLINEFORM0 most frequently occurring words, that occur at least some number INLINEFORM1 times. It is implemented in Spark as a straight-forward map-reduce job.
answer:

Do they perform any morphological tokenization?