instruction:
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.
question:
In order to derive the discourse features, an entity grid is constructed by feeding the document through an NLP pipeline to identify salient entities. Two flavors of discourse features are created by populating the entity grid with either (i) grammatical relations (GR) or (ii) RST discourse relations (RST).  
 Question: What discourse features are used?
answer:
Entity grid with grammatical relations and RST discourse relations.


question:
Pre-trained English NER model We construct the English NER system following BIBREF7 . This system uses a bidirectional LSTM as a character-level language model to take context information for word embedding generation.  For pre-trained English NER system, we use the default NER model of Flair. 
 Question: Which pre-trained English NER model do they use?
answer:
Bidirectional LSTM based NER model of Flair


question:
We choose Zulu (ZUL), a Bantoid language. In contrast to the first two, it is strongly prefixing. 
 Question: What is an example of a prefixing language?
answer:

Zulu