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.

Example Input: GP-GNNs first build a fully-connected graph $\mathcal {G} = (\mathcal {V}, \mathcal {E})$ , where $\mathcal {V}$ is the set of entities, and each edge $(v_i, v_j) \in \mathcal {E}, v_i, v_j \in \mathcal {V}$ corresponds to a sequence $s = x_0^{i,j}, x_1^{i,j}, \dots , x_{l-1}^{i,j}$ extracted from the text.  
 Question: So this paper turns unstructured text inputs to parameters that GNNs can read?
Example Output: Yes-no

Example Input: In this section, we present the details of the analysis performed on the data obtained pertaining to Twitter messages from January 2020 upto now, that is the time since the news of the Coronavirus outbreak in China was spread across nations. Also, the data prominently captures the tweets in English, Spanish, and French languages. 
 Question: Do they collect only English data?
Example Output: Yes-no

Example Input: In this section, we present the details of the analysis performed on the data obtained pertaining to Twitter messages from January 2020 upto now, that is the time since the news of the Coronavirus outbreak in China was spread across nations. Also, the data prominently captures the tweets in English, Spanish, and French languages. 
 Question: Do they collect only English data?
Example Output:
Yes-no