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.

[Q]: In this paper we propose two neural embedding models in order to learn continuous concept vectors based on the skip-gram model BIBREF11 . Our first model is the Concept Raw Context model (CRC) which utilizes concept mentions in a large scale KB to jointly learn embeddings of both words and concepts. Our second model is the Concept-Concept Context model (3C) which learns the embeddings of concepts from their conceptual contexts (i.e., contexts containing surrounding concepts only).  
 Question: What are the two neural embedding models?
[A]: Our first model is the Concept Raw Context model (CRC) which utilizes concept mentions in a large scale KB to jointly learn embeddings of both words and concepts. Our second model is the Concept-Concept Context model (3C) which learns the embeddings of concepts from their conceptual contexts (i.e., contexts containing surrounding concepts only)


[Q]: The English online magazine of ISIS was named Dabiq and first appeared on the dark web on July 2014 and continued publishing for 15 issues. This publication was followed by Rumiyah which produced 13 English language issues through September 2017. Looking through both Dabiq and Rumiyah, many issues of the magazines contain articles specifically addressing women, usually with “ to our sisters ” incorporated into the title. 
 Question: Do they report results only on English data?
[A]: Yes


[Q]: Internally, the ASR system maintains a rich hypothesis space in the form of speech lattices or confusion networks (cnets). 
 Question: What is a word confusion network?
[A]:
It is a network used to encode speech lattices to maintain a rich hypothesis space.