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.

[Q]: We recognise features that add ambiguity to the supporting facts, for example when information is only expressed implicitly by using an Ellipsis. As opposed to redundant words, we annotate Restrictivity and Factivity modifiers, words and phrases whose presence does change the meaning of a sentence with regard to the expected answer, and occurrences of intra- or inter-sentence Coreference in supporting facts (that is relevant to the question). Lastly, we mark ambiguous syntactic features, when their resolution is required in order to obtain the answer. Concretely, we mark argument collection with con- and disjunctions (Listing) and ambiguous Prepositions, Coordination Scope and Relative clauses/Adverbial phrases/Appositions. We recognise features that add ambiguity to the supporting facts, for example when information is only expressed implicitly by using an Ellipsis. As opposed to redundant words, we annotate Restrictivity and Factivity modifiers, words and phrases whose presence does change the meaning of a sentence with regard to the expected answer, and occurrences of intra- or inter-sentence Coreference in supporting facts (that is relevant to the question). Lastly, we mark ambiguous syntactic features, when their resolution is required in order to obtain the answer. Concretely, we mark argument collection with con- and disjunctions (Listing) and ambiguous Prepositions, Coordination Scope and Relative clauses/Adverbial phrases/Appositions. 
 Question: What features are absent from MRC gold standards that can result in potential lexical ambiguity?
[A]: Extractive


[Q]: We employ precision, recall, F1 and accuracy for evaluation metrics. 
 Question: what evaluation metrics are reported?
[A]: Extractive


[Q]: We introduce a list of 8 different competencies that a reading system should master in order to process reviews and text documents in general. These 8 tasks require different competencies and a different level of understanding of the document to be well answered. For instance, detecting if an aspect is mentioned in a review will require less understanding of the review than predicting explicitly the rating of this aspect. Table TABREF10 presents the 8 tasks we have introduced in this dataset with an example of a question that corresponds to each task. 
 Question: What kind of questions are present in the dataset?
[A]:
Extractive