Collaborative Annotation for Reliable Natural Language by Kar?n Fort

By Kar?n Fort

This ebook provides a distinct chance for developing a constant photo of collaborative guide annotation for normal Language Processing (NLP).  NLP has witnessed significant evolutions long ago 25 years: first of all, the extreme good fortune of computing device studying, that is now, for larger or for worse, overwhelmingly dominant within the box, and secondly, the multiplication of overview campaigns or shared projects. either contain manually annotated corpora, for the educational and overview of the systems.

These corpora have gradually develop into the hidden pillars of our area, delivering meals for our hungry laptop studying algorithms and reference for evaluate. Annotation is now where the place linguistics hides in NLP. although, handbook annotation has principally been neglected for your time, and it has taken it slow even for annotation directions to be well-known as essential.

Although a few efforts were made in recent years to handle the various matters offered by means of handbook annotation, there has nonetheless been little examine performed at the topic. This booklet goals to supply a few precious insights into the subject.

Manual corpus annotation is now on the center of NLP, and remains to be principally unexplored. there's a want for handbook annotation engineering (in the feel of a accurately formalized process), and this e-book goals to supply a primary step in the direction of a holistic method, with a world view on annotation.

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Extra info for Collaborative Annotation for Reliable Natural Language Processing: Technical and Sociological Aspects

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It also covers the cases in which the annotators have to access unpredicted sources of knowledge OR have to read the whole text to be able to annotate. Finally, 1 is for cases where the annotators both have to consult previously unidentified sources of knowledge AND the whole data flow (usually, text). 12. The context as a complexity dimension: two sub-dimensions to take into account The gene renaming task is very complex from that point of view (1), as it required the annotators to read the whole text and they sometimes needed to consult new external sources.

Four options are available: 1) publish the corpus, which is considered to be in a sufficiently satisfactory state to be final; 2) review the corpus and adapt the annotation guide; 3) adjudicate the corpus; 4) give up on revision and publication (failure). In most cases, a correction phase is necessary. 7 In case there is a correction (adjudication and reviewing), the corpus has to be evaluated and be submitted, with its indicators, to the decision of the manager, who can either publish the corpus or have it corrected again.

Synthesis of the complexity of the gene names renaming campaign (new scale x2) Annotating Collaboratively 43 Note that the decomposition into EATs does not imply a simplification of the original task, as is often the case for Human Intelligence Tasks (HITs) performed by Turkers (workers) on Amazon Mechanical Turk (see, for example, [COO 10a]). 3. Annotation tools Once the complexity profile is established, the manager has a precise vision of the campaign and can select an appropriate annotation tool.

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