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.

Example Input: 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?
Example Output: Bayesian model of garg2012unsupervised as our base monolingual model

Example Input: VQA research began in earnest in late 2014 when the DAQUAR dataset was released BIBREF0 
 Question: From when are many VQA datasets collected?
Example Output: late 2014

Example Input: We use the following three evaluation metrics:

Phoneme Error Rate (PER) is the Levenshtein distance between the predicted phoneme sequences and the gold standard phoneme sequences, divided by the length of the gold standard phoneme sequences.

Word Error Rate (WER) is the percentage of words in which the predicted phoneme sequence does not exactly match the gold standard phoneme sequence.

Word Error Rate 100 (WER 100) is the percentage of words in the test set for which the correct guess is not in the first 100 guesses of the system. 
 Question: what evaluation metrics were used?
Example Output:
Phoneme Error Rate (PER) Word Error Rate (WER) Word Error Rate 100 (WER 100)