

Here's what the individual fields represent:
* id: the example's id
* image: a PIL.Image.Image object containing the document image
* query: the question string - natural language asked question, in several languages
* answers: a list of correct answers provided by human annotators
* words and bounding_boxes: the results of OCR, which we will not use here
* answer: an answer matched by a different model which we will not use here
Let's leave only English questions, and drop the answer feature which appears to contain predictions by another model.
We'll also take the first of the answers from the set provided by the annotators. Alternatively, you can randomly sample it.