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.

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?
Zulu

Figure FIGREF23 shows the proposed ontology, which, in our evaluation procedure, was populated with 3121 events entries from 51 documents. 
 Question: How is the effectiveness of this pipeline approach evaluated?
proposed ontology, which, in our evaluation procedure, was populated with 3121 events entries from 51 documents.

Logistic regression: To produce the representation of the input, we concatenate the Bag-Of-Words representation of the document with the Bag-Of-Words representation of the question. LSTM: We start with a concatenation of the sequence of indexes of the document with the sequence of indexes of the question. Them we feed an LSTM network with this vector and use the final state as the representation of the input. Finally, we apply a logistic regression over this representation to produce the final decision. End-to-end memory networks: This architecture is based on two different memory cells (input and output) that contain a representation of the document. Deep projective reader: This is a model of our own design, largely inspired by the efficient R-net reader BIBREF12 . 
 Question: What baselines are presented?

Logistic regression LSTM End-to-end memory networks Deep projective reader