TASK DEFINITION: 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.
PROBLEM: Our method is purely text-based, and ignores the publication date and the source of the article. It combines task-specific embeddings, produced by a two-level attention-based deep neural network model, with manually crafted features (stylometric, lexical, grammatical, and semantic), into a kernel-based SVM classifier.
Question: what types of features were used?

SOLUTION: stylometric, lexical, grammatical, and semantic

PROBLEM: The previously mentioned datasets are all in English
Question: For which languages most of the existing MRC datasets are created?

SOLUTION: English

PROBLEM: We created our own causal explanation dataset by collecting 3,268 random Facebook status update messages.
Question: What types of social media did they consider?

SOLUTION:
Facebook status update messages