Chapter 3. Annotation Literal Concepts

Now that you know all about the high-level concerns of Training Data, how do we start to put some of these concepts into practice?

In this chapter we start to dive into the heart of actually getting data into your system, configuring it, and getting data out to your models. And I’ll cover the nitty gritty of actually doing annotations. Let’s dive in!

First a quick refresher on Schema. Schema may be as simple as a set of labels, like “valid”, “invalid”, “unsure”, or as complex as many nested attributes and relations. More generally, it’s a paradigm for encoding Who, What, Where, How & Why. A representation of meaning structured by Labels, Attributes, and their Relation to each other. 

Chapter Organization: Administrators and Annotators

This chapter is made of two parts. The first is focused on the Administrator’s view and the second for the Annotator. Like any ...

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