International Workshop on Systems and Frameworks for Computational Morphology

Systems and Frameworks for Computational Morphology pp 94-103 | Cite as

Dsolve—Morphological Segmentation for German Using Conditional Random Fields

Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 537)


We describe Dsolve, a system for the segmentation of morphologically complex German words into their constituent morphs. Our approach treats morphological segmentation as a classification task, in which the locations and types of morph boundaries are predicted by a Conditional Random Field model trained from manually annotated data. The prediction of morph-boundary types in addition to their locations distinguishes Dsolve from similar approaches previously suggested in the literature. We show that the use of boundary types provides a (somewhat counter-intuitive) performance boost with respect to the simpler task of predicting only segment locations.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Berlin-Brandenburg Academy of Sciences and HumanitiesBerlinGermany

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