Something Borrowed, Something Blue: Rule-based Combination of POS Taggers

Linguistically annotated text resources are still scarce for many languages and for many text types, mainly because their creation represents a major investment of work and time. For this reason, it is worthwhile to investigate ways of reusing existing resources in novel ways. In this paper, we investigate how off-the-shelf part of speech (POS) taggers can be combined to better cope with text material of a type on which they were not trained, and for which there are no readily available training corpora. We indicate—using freely available taggers for German (although the method we describe is not language-dependent)—how such taggers can be combined by using linguistically motivated rules so that the tagging accuracy of the combination exceeds that of the best of the individual taggers.

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