In this task, you will be presented with a context from an academic paper and a question separated with a
. You have to answer the question based on the context.

[EX Q]: Automation of cQA forums can be divided into three tasks: question-comment relevance (Task A), question-question relevance (Task B), and question-external comment relevance (Task C). In our cQA tasks, the pair of objects are (question, question) or (question, comment), and the relationship is relevant/irrelevant. For task C, in addition to an original question (oriQ) and an external comment (relC), the question which relC commented on is also given (relQ). To incorporate this extra information, we consider a multitask learning framework which jointly learns to predict the relationships of the three pairs (oriQ/relQ, oriQ/relC, relQ/relC).
Question: What supplemental tasks are used for multitask learning?
[EX A]: Multitask learning is used for the task of predicting relevance of a comment on a different question to a given question, where the supplemental tasks are predicting relevance between the questions, and between the comment and the corresponding question

[EX Q]: An extrinsic evaluation was carried out on the task of Open IE BIBREF7.
Question: Is the semantic hierarchy representation used for any task?
[EX A]: Yes, Open IE

[EX Q]: In contrast, our models are trained only on the 76K questions in the training set.
Question: Do the authors also try the model on other datasets?
[EX A]:
No