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.

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?
Their accuracy in word segmentation is about 94%-97%.

We compare our personalized models against two baselines. The first is a name-based Nearest-Neighbor model (NN). We initially adapted the Neural Checklist Model of BIBREF0 as a baseline; however, we ultimately use a simple Encoder-Decoder baseline with ingredient attention (Enc-Dec), which provides comparable performance and lower complexity.
Question: What are the baseline models?
name-based Nearest-Neighbor model (NN) Encoder-Decoder baseline with ingredient attention (Enc-Dec)

We use the Yelp Challenge dataset BIBREF2 for our fake review generation.
Question: Which dataset do they use a starting point in generating fake reviews?
the Yelp Challenge dataset