A Rule-Based Unsupervised Morphology Learning Framework.
Constantine Lignos, Erwin Chan, Mitchell P. Marcus, Charles D Yang · CLEF (Working Notes) · 2009
We use the Base and Transforms Model proposed by Chan [1] as the core of a morphological analyzer, extending its concept of base-derived relationships to allow multi-step derivations and adding a number of features required for robustness on larger corpora. The result is a rule-based morphological analyzer, attaining an F-score of 58.48% in English and 33.61% in German in the Morphochallenge 2009 Competition 1 evaluation.