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.

Example Input: Four factual attributes pertaining to the 200 colleges are extracted from the U.S. News Statistics, which consists of Undergraduate Enrollment, Male/Female Ratio, Private/Public, and Region (Northeast, South, West, and Midwest).
Question: Which major geographical regions are studied?
Example Output: Northeast U.S, South U.S., West U.S. and Midwest U.S.

Example Input: Our system, including software and corpus, is available as an open source project for free research purpose and we believe that it is a good baseline for the development and comparison of future Vietnamese SRL systems.
Question: Are their corpus and software public?
Example Output: Yes

Example Input: A causal attribution dataset is a collection of text pairs that reflect cause-effect relationships proposed by humans (for example, "virus causes sickness"). These written statements identify the nodes of the network (see also our graph fusion algorithm for dealing with semantically equivalent statements) while cause-effect relationships form the directed edges ("virus" $
ightarrow $ "sickness") of the causal attribution network.
Question: What are causal attribution networks?
Example Output:
networks where nodes represent causes and effects, and directed edges represent cause-effect relationships proposed by humans