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:
For our classification experiments, we use the MH17 Twitter dataset introduced by BIBREF4, a dataset collected in order to study the flow of (dis)information about the MH17 plane crash on Twitter.
answer:
What dataset is used for this study?

question:
We adapted BERTNLU from ConvLab-2. We implemented a rule-based model (RuleDST) and adapted TRADE (Transferable Dialogue State Generator) BIBREF19 in this experiment. We adapted a vanilla policy trained in a supervised fashion from ConvLab-2 (SL policy).
answer:
What are the benchmark models?

question:
The dataset needed to train the W2V was obtained using the information extracted from a dump of the Italian Wikipedia (dated 2019.04.01), from the main categories of Italian Google News (WORLD, NATION, BUSINESS, TECHNOLOGY, ENTERTAINMENT, SPORTS, SCIENCE, HEALTH) and from some anonymized chats between users and a customer care chatbot (Laila).
answer:
What dataset is used for training Word2Vec in Italian language?