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: Our study focused primarily on English tweets, since this was the language of our diagnostic training sample. 
 Question: Do the authors report results only on English datasets?
Example Output: Yes

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

Example Input: To further improve the performance, we adopt system combination on the decoding lattice level. By combining systems, we can take advantage of the strength of each model that is optimized for different domains.  The best result for vlsp2018 of 4.85% WER is obtained by the combination weights 0.6:0.4 where 0.6 is given to the general language model and 0.4 is given to the conversation one. On the vlsp2019 set, the ratio is change slightly by 0.7:0.3 to deliver the best result of 15.09%. 
 Question: What is the language model combination technique used in the paper?
Example Output:
system combination on the decoding lattice level combination weights

