In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.

[EX Q]: Compared with the BERT-BASE model, BERT-SPC significantly improves the accuracy and F1 score of aspect polarity classification.
[EX A]: How much better is performance of the proposed model compared to the state of the art in these various experiments?

[EX Q]: To evaluate the proposed BiLSTM model with attention (BiLSTM+att), it is compared with three of its own variants: a BiLSTM without attention (BiLSTM) as well as a single forward-LSTM layer with attention (LSTM+att) and without attention (LSTM). Additional baselines are defined by BIBREF32 who already proposed an LSTM-based architecture that only uses non-temporal features, and the SVM-based estimation model as originally used for reward estimation by BIBREF24.
[EX A]: What model do they use a baseline to estimate satisfaction?

[EX Q]: We use TB-Dense and MATRES in our experiments and briefly summarize the data statistics in Table TABREF33.
[EX A]:
What datasets were used for this work?