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.

Ex Input:
The word intrusion test is expensive to apply since it requires manual evaluations by human observers separately for each embedding dimension. Furthermore, the word intrusion test does not quantify the interpretability levels of the embedding dimensions, instead it yields a binary decision as to whether a dimension is interpretable or not. However, using continuous values is more adequate than making binary evaluations since interpretability levels may vary gradually across dimensions. 
 Question: What advantages does their proposed method of quantifying interpretability have over the human-in-the-loop evaluation they compare to?

Ex Output:
it is less expensive and quantifies interpretability using continuous values rather than binary evaluations


Ex Input:
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?

Ex Output:
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


Ex Input:
The joke corpus in this dataset contains thousands of unique jokes of different categories (sci-fi, sports, etc) and types (puns, limerick, etc). 
 Question: Where did the real production data come from?

Ex Output:

 jokes of different categories (sci-fi, sports, etc) and types (puns, limerick, etc)