In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.

Ex Input:
We use data from Mandarin Chinese and Cantonese. For each language, the data consists of a list of spoken words, recorded by the same speaker. The Mandarin dataset is from a female speaker and is provided by Shtooka, and the Cantonese dataset is from a male speaker and is downloaded from Forvo, an online crowd-sourced pronunciation dictionary.

Ex Output:
What dataset is used for training?


Ex Input:
The resulting set of 46 documents makes up our base corpus. Note that these documents vary greatly in size, which means the resulting corpus is varied, but not balanced in terms of size (Table TABREF43).

Ex Output:
How big PIE datasets are obtained from dictionaries?


Ex Input:
The baseline applies linear logistic regression to a set of stock technical signals to predict the following day’s stock return sign (+/‐). No sentiment features are provided to the baseline model.

Ex Output:

What is the baseline machine learning prediction approach?