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 final embedding dimensionality is equal to the number of unique word labels in the training set, which is 1061.
Question: Which dimensionality do they use for their embeddings?

Ex Output:
1061

Ex Input:
Table TABREF14 show the results obtained for proposed s2sL approach in comparison to that of MLP for the tasks of Speech/Music and Neutral/Sad classification, by considering different proportions of training data.
Question: Which models/frameworks do they compare to?

Ex Output:
MLP

Ex Input:
The dataset consists of queries and the corresponding image search results. Each token in each query is given a language tag based on the user-set home language of the user making the search on Google Images.
Question: Do the images have multilingual annotations or monolingual ones?

Ex Output:
monolingual