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.

Ex Input:
The corpus used for sentiment analysis is the IMDb dataset of movie reviews by BIBREF11 while that for NER is Groningen Meaning Bank (GMB) by BIBREF12, containing 47,959 sentence samples.
Question: What sentiment analysis dataset is used?

Ex Output:
IMDb dataset of movie reviews

Ex Input:
The best baseline model is NO-MOVE, reaching an accuracy of 30.3% on single sentences and 0.3 on complete paragraphs.
Question: How well did the baseline perform?

Ex Output:
accuracy of 30.3% on single sentences and 0.3 on complete paragraphs

Ex Input:
In general, the baseline model CAEVO is outperformed by both NN models, and NN model with BERT embedding achieves the greatest performance.
Question: Do the BERT-based embeddings improve results?

Ex Output:
Yes