instruction:
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.
question:
The annotator carried out all annotation. 
 Question: How many annotators tagged each tweet?
answer:
One


question:
We propose to derive rewards from human-human dialogues by assigning positive values to contextualised responses seen in the data, and negative values to randomly chosen responses due to lacking coherence (also referred to as `non-human-like responses') – see example in Tables TABREF29 and TABREF30 . 
 Question: How do they obtain human generated policies?
answer:
derive rewards from human-human dialogues by assigning positive values to contextualised responses seen in the data, and negative values to randomly chosen responses due to lacking coherence


question:
The speech content was obtained from the closed captions (CC) provided by the YouTube ASR system which can be though as subtitles. 
 Question: What ASR system do they use?
answer:

YouTube ASR system