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:
We evaluate our proposed model on a Twitter dataset obtained from the authors of BIBREF12. Our final dataset consists of 11,576 users (i.e, fact-checkers), 4,732 fact-checking URLs and 63,429 interactions. The dataset also contains each user's social network information. Note that each user's social relationship is restricted within available users in the dataset. 
 Question: What dataset is used?
answer:
Twitter dataset obtained from the authors of BIBREF12


question:
Based on annotated corpora and token-based features, studies used machine learning approaches to build word segmentation systems with accuracy about 94%-97%. 
 Question: How successful are the approaches used to solve word segmentation in Vietnamese?
answer:
Their accuracy in word segmentation is about 94%-97%.


question:
The improved performance of our attention models that actively select their optimal context, over a model with the complete thread as context, hLSTM, shows that the context inference improves intervention prediction over using the default full context. 
 Question: What aspects of discussion are relevant to instructor intervention, according to the attention mechanism?
answer:

context inference