instruction:
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.
question:
The overall Total Accuracy score reported in table TABREF19 using the entire feature set is 549. 
answer:
Do they experiment with the dataset?


question:
Our method is purely text-based, and ignores the publication date and the source of the article. It combines task-specific embeddings, produced by a two-level attention-based deep neural network model, with manually crafted features (stylometric, lexical, grammatical, and semantic), into a kernel-based SVM classifier.
answer:
what types of features were used?


question:
We train an LSTM with and without attention on the training set. After training, we take the best model in terms of BLEU score BIBREF16 on the development set and calculate the BLEU score on the test set. 
answer:

How is the generative model evaluated?