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:
We use Waseem and Hovy BIBREF5, Davidson et al. BIBREF9, and Waseem et al. BIBREF10 as baselines and compare the results with our different fine-tuning strategies using pre-trained BERTbase model.
Question: What baseline is used?

Ex Output:
Waseem and Hovy BIBREF5 Davidson et al. BIBREF9 Waseem et al. BIBREF10

Ex Input:
The primary feed for the analysis collected INLINEFORM0 million tweets containing the keywords 'breast' AND 'cancer'.
Question: How were breast cancer related posts compiled from the Twitter streaming API?

Ex Output:
By using keywords 'breast' AND 'cancer' in tweet collecting process.

Ex Input:
We provide three pairs of short/long datasets from different domains (movies and restaurants) and from different languages (English and Korean) suitable for the task: Mov_en, Res_en, and Mov_ko. Most of the datasets are from previous literature and are gathered differently The Mov_en datasets are gathered from different websites; the short dataset consists of hand-picked sentences by BIBREF19 from document-level reviews from the Rotten Tomatoes website, while the long dataset consists of reviews from the IMDB website obtained by BIBREF20.
Question: What dierse domains and languages are present in new datasets?

Ex Output:
movies restaurants English Korean