This book is intended as a resource for people who are interested in using computers to
help process natural language. A natural language refers to any language spoken by
humans, either currently (e.g., English, Chinese, Spanish) or in the past (e.g., Latin,
ancient Greek, Sanskrit). Annotation refers to the process of adding metadata informa
tion to the text in order to augment a computer’s capability to perform Natural Language
Processing (NLP). In particular, we examine how information can be added to natural
language text through annotation in order to increase the performance of machine
learning algorithms—computer programs designed to extrapolate rules from the infor
mation provided over texts in order to apply those rules to unannotated texts later on.
Create your own natural language training corpus for machine learning. Whether you’re working with English, Chinese, or any other natural language, this hands-on book guides you through a proven annotation development cycle—the process of adding metadata to your training corpus to help ML algorithms work more efficiently. You don’t need any programming or linguistics experience to get started.
Using detailed examples at every step, you’ll learn how the MATTER Annotation Development Process helps you Model, Annotate, Train, Test, Evaluate, and Revise your training corpus. You also get a complete walkthrough of a real-world annotation project.
Define a clear annotation goal before collecting your dataset (corpus)
Learn tools for analyzing the linguistic content of your corpus
Build a model and specification for your annotation project
Examine the different annotation formats, from basic XML to the Linguistic Annotation Framework
Create a gold standard corpus that can be used to train and test ML algorithms
Select the ML algorithms that will process your annotated data
Evaluate the test results and revise your annotation task
Learn how to use lightweight software for annotating texts and adjudicating the annotations
This book is a perfect companion to O’Reilly’s Natural Language Processing with Python.