Annotation

Citation: Eduard Hovy (2010) Annotation. Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics (RSS)

Download: http://aclweb.org/anthology-new/P/P10/P10-5004.pdf

Tagged: Computer Science (RSS) annotation (RSS), annotations (RSS)

Summary:

This tutorial views annotation as a science, with clear steps.

Corpus selection

Consider availability (existing corpora) and openness (so others can evaluate and build on your work).
Consider representativeness
- Different corpora will be appropriate for different purposes

Annotation guidelines are essential. These must be developed iteratively.
There's a tradeoff between the granularity of the categories and the practical attainability. Use as few categories as possible and make distinctions between them clear.
Measure interannotator agreement and disagreement:
- "Precision" measures the correctness of annotators (compared to a gold standard); it corresponds to how easy the categorization is. See Generalized estimating equations for correlated binary data: Using the odds ratio as a measure of association <math>P_i = number correct/N</math>
- "Entropy" measures ambiguity (clarity of definitions). <math>E_i = -\sum_iP_i</math> See Generalized estimating equations for correlated binary data: Using the odds ratio as a measure of association

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Krippendorff, K. 2007. Computing Krippendorff’s Alpha reliability. papers/43 exact method, with example matrices online
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Theoretical and practical relevance:

Annotation is widely used. For example,

Other useful annotation tools and resources include:

Sample Corpora and corpora sources