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 use the Bayesian model of garg2012unsupervised as our base monolingual model. The semantic roles are predicate-specific. 
 Question: What does an individual model consist of?
Bayesian model of garg2012unsupervised as our base monolingual model

We present a comparison of the proposed models to existing word embeddings approaches. These are: the Bernoulli embeddings (b-emb) BIBREF1 , continuous bag-of-words (CBOW) BIBREF5 , Distributed Memory version of Paragraph Vector (PV-DM) BIBREF11 and the Global Vectors (GloVe) BIBREF6 model. 
 Question: What word embeddings do they test?
Bernoulli embeddings (b-emb) BIBREF1 , continuous bag-of-words (CBOW) BIBREF5 , Distributed Memory version of Paragraph Vector (PV-DM) BIBREF11 and the Global Vectors (GloVe) BIBREF6 model

In the first scenario we equip the decoder with an additional morphology table including target-side affixes. 
 Question: What type of morphological information is contained in the "morphology table"?

target-side affixes

