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.

Input: Consider Input: The only remaining question is what makes two environments similar enough to infer the existence of a common category. There is, again, a large literature on this question (including the aforementioned language modeling, unsupervised parsing, and alignment work), but in the current work we will make use of a very simple criterion: fragments are interchangeable if they occur in at least one lexical environment that is exactly the same.
Question: How do they determine similar environments for fragments in their data augmentation scheme?

Output: fragments are interchangeable if they occur in at least one lexical environment that is exactly the same

Input: Consider Input: The ensembles were formed by simply averaging the predictions from the constituent single models.
Question: How does their ensemble method work?

Output: simply averaging the predictions from the constituent single models

Input: Consider Input: Fourteen such feature extractors have been implemented which can be clubbed into 3 major categories:

[noitemsep]

Lexicon Features

Word Vectors

Syntax Features
Question: how many total combined features were there?
Output: Fourteen