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: For example, it can be used to extract features for usage with other machine learning tools, or to evaluate given features with the existing classifiers or regressors. Figure FIGREF19 demonstrates a simple feature extractor that retrieves the sentence length.
Question: Do they show an example of usage for INFODENS?
Example Output: Yes

Example Input: We observe interesting hidden correlation in data. Fig. FIGREF24 has Topic 2 as selected topic. Topic 2 contains top-4 co-occurring keywords "vegan", "yoga", "job", "every_woman" having the highest term frequency. We can infer different things from the topic that "women usually practice yoga more than men", "women teach yoga and take it as a job", "Yogi follow vegan diet". We would say there are noticeable correlation in data i.e. 'Yoga-Veganism', 'Women-Yoga'. Women-Yoga
Question: What other interesting correlations are observed?
Example Output: Women-Yoga

Example Input: Specifically, PlEWi supplied 550,755 [error, correction] pairs, from which 298,715 were unique.
Question: How is PIEWi annotated?
Example Output:
[error, correction] pairs