Collaborative Annotation for Reliable Natural Language Processing

Collaborative Annotation for Reliable Natural Language Processing
Author :
Publisher : John Wiley & Sons
Total Pages : 192
Release :
ISBN-10 : 9781848219045
ISBN-13 : 1848219040
Rating : 4/5 (040 Downloads)

Book Synopsis Collaborative Annotation for Reliable Natural Language Processing by : Karën Fort

Download or read book Collaborative Annotation for Reliable Natural Language Processing written by Karën Fort and published by John Wiley & Sons. This book was released on 2016-06-13 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a unique opportunity for constructing a consistent image of collaborative manual annotation for Natural Language Processing (NLP). NLP has witnessed two major evolutions in the past 25 years: firstly, the extraordinary success of machine learning, which is now, for better or for worse, overwhelmingly dominant in the field, and secondly, the multiplication of evaluation campaigns or shared tasks. Both involve manually annotated corpora, for the training and evaluation of the systems. These corpora have progressively become the hidden pillars of our domain, providing food for our hungry machine learning algorithms and reference for evaluation. Annotation is now the place where linguistics hides in NLP. However, manual annotation has largely been ignored for some time, and it has taken a while even for annotation guidelines to be recognized as essential. Although some efforts have been made lately to address some of the issues presented by manual annotation, there has still been little research done on the subject. This book aims to provide some useful insights into the subject. Manual corpus annotation is now at the heart of NLP, and is still largely unexplored. There is a need for manual annotation engineering (in the sense of a precisely formalized process), and this book aims to provide a first step towards a holistic methodology, with a global view on annotation.


Collaborative Annotation for Reliable Natural Language Processing Related Books