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: This action space is of the order of $A=\mathcal {O}(|V| \times |O|^2)$ where $V$ is the number of action verbs, and $O$ is the number of distinct objects in the world that the agent can interact with. As this is too large a space for a RL agent to effectively explore, the knowledge graph is used to prune this space by ranking actions based on their presence in the current knowledge graph and the relations between the objects in the graph as in BIBREF7 
 Question: How is the domain knowledge transfer represented as knowledge graph?

SOLUTION: the knowledge graph is used to prune this space by ranking actions based on their presence in the current knowledge graph and the relations between the objects in the graph as in BIBREF7

PROBLEM: We crowdsourced multiple-choice questions in two parts, encouraging workers to be imaginative and varied in their use of language. First, workers were given a seed qualitative relation q+/-( INLINEFORM0 ) in the domain, expressed in English (e.g., “If a surface has more friction, then an object will travel slower”), and asked to enter two objects, people, or situations to compare. 
 Question: Do all questions in the dataset allow the answers to pick from 2 options?

SOLUTION: Yes

PROBLEM: In this paper we present our work, which is a part of the SociaL Media And Harassment Competition of the ECML PKDD 2019 Conference.   We are using the dataset of the competition, which includes text from tweets having the aforementioned categories. 
 Question: What were the datasets used in this paper?

SOLUTION:
The dataset from the SociaL Media And Harassment Competition of the ECML PKDD 2019 Conference. 

