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: Both the audio and the transcript are de-identified (by removing the identifying information) with digital zeros and [de-identified] tags, respectively. 
 Question: Is the data de-identified?

A: Yes
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Q: We use the Bayesian model of garg2012unsupervised as our base monolingual model. The semantic roles are predicate-specific. 
 Question: What does an individual model consist of?

A: Bayesian model of garg2012unsupervised as our base monolingual model
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Q: All documents are segmented into paragraphs and processed at the paragraph level (both training and inference); this is acceptable because we observe that most paragraphs are less than 200 characters. The input sequences are segmented by the BERT tokenizer, with the special [CLS] token inserted at the beginning and the special [SEP] token added at the end. 
 Question: Was the structure of regulatory filings exploited when training the model? 

A:
No
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