This publication offers a different chance for developing a constant snapshot of collaborative guide annotation for traditional Language Processing (NLP).  NLP has witnessed significant evolutions some time past 25 years: to start with, the intense good fortune of desktop studying, that's now, for larger or for worse, overwhelmingly dominant within the box, and secondly, the multiplication of evaluate campaigns or shared projects. either contain manually annotated corpora, for the educational and assessment of the systems.

These corpora have gradually turn into the hidden pillars of our area, offering meals for our hungry laptop studying algorithms and reference for overview. Annotation is now where the place linguistics hides in NLP. although, guide annotation has principally been missed for it slow, and it has taken some time even for annotation instructions to be well-known as essential.

Although a few efforts were made in recent years to handle many of the concerns awarded via guide annotation, there has nonetheless been little study performed at the topic. This booklet goals to supply a few helpful insights into the subject.

Manual corpus annotation is now on the middle of NLP, and continues to be mostly unexplored. there's a want for guide annotation engineering (in the experience of a accurately formalized process), and this e-book goals to supply a primary step in the direction of a holistic method, with an international view on annotation.


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