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.

Input: Consider Input: 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. 
 Question: Do they perform any morphological tokenization?

Output: No


Input: Consider Input: The contributions of this work are: 
 Question: Do they look for inconsistencies between different UD treebanks?

Output: Yes


Input: Consider Input: Same as BIBREF5 , in the first sub-network, pinyin sequence is predicted from the video. Different from BIBREF5 , which predicts pinyin characters from video, pinyin is taken as a whole in CSSMCM, also known as syllables. As we know, Mandarin Chinese is a syllable-based language and syllables are their logical unit of pronunciation. 
 Question: What syntactic structure is used to model tones?


Output: syllables