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.
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Question: 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.

Answer: What are the baseline models?

Question: To help the human representative quickly determine the cause of the escalation, we generate a visualization of the user's turns using the attention weights to highlight the turns influential in the escalation decision.

Answer: Do they explain model predictions solely on attention weights?

Question: The same 36 questions were answered using four QALD tools: WDAqua BIBREF0 , QAKiS BIBREF7 , gAnswer BIBREF6 and Platypus BIBREF8 .

Answer:
Which four QA systems do they use?