In this task, you will be presented with a context from an academic paper and a question based on the context. You have to classify the questions into "Extractive", "Abstractive", or "Yes-no" questions. Extractive questions can be answered by concatenating extracts taken from a context into a summary while answering abstractive questions involves paraphrasing the context using novel sentences. Yes-no question is a question whose expected answer is one of two choices, one that affirms the question and one that denies the question. Typically, the choices are either yes or no.
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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). The dataset (composed of 2.6 GB of raw text) includes $421\,829\,960$ words divided into $17\,305\,401$ sentences. All the words were then transformed to lowercase (to avoid a double presence) finally producing a vocabulary of $618\,224$ words. 
 Question: What is the dataset used as input to the Word2Vec algorithm?

Answer: Abstractive


Question: The SemEval-2010 benchmark dataset BIBREF0 is composed of 244 scientific articles collected from the ACM Digital Library (conference and workshop papers). 
 Question: how many articles are in the dataset?

Answer: Extractive


Question: The English online magazine of ISIS was named Dabiq and first appeared on the dark web on July 2014 and continued publishing for 15 issues. This publication was followed by Rumiyah which produced 13 English language issues through September 2017. Looking through both Dabiq and Rumiyah, many issues of the magazines contain articles specifically addressing women, usually with “ to our sisters ” incorporated into the title. 
 Question: Do they report results only on English data?

Answer:
Yes-no