27 janvier 2012
Young-Min Kim, « Upper bound of annotation with proper noun features », BILBO – Automatic Annotation of Bibliographical References, ID : 10670/1.4r7qkl
An idea, which naturally stuck us, is to try out learning a model with a complete proper noun feature set for each strategy. It will give us an objective upper bound on the annotation performance. And from the expected upper bounds, we can decide which strategy is preferable that the others. The question here is how to complete proper noun lists. We figure out this problem by artificially attaching proper noun features from the real labels. For example, if a token has ‘surname’ label we atta...