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.

[Q]: We recruited 100 crowdworkers on Amazon Mechanical Turk (AMT) and measured completion times and accuracies for typing randomly sampled sentences from the Yelp corpus.
Question: What user variations have been tested?
[A]: completion times and accuracies

[Q]: Our method is purely text-based, and ignores the publication date and the source of the article. It combines task-specific embeddings, produced by a two-level attention-based deep neural network model, with manually crafted features (stylometric, lexical, grammatical, and semantic), into a kernel-based SVM classifier.
Question: what types of features were used?
[A]: stylometric, lexical, grammatical, and semantic

[Q]: This allows Macaw to support multi-modal interactions, such as text, speech, image, click, etc.
Question: What modalities are supported by Macaw?
[A]:
text, speech, image, click, etc