Labeled Morphological Segmentation with Semi-Markov Models
Ryan Cotterell Thomas Müller Alexander Fraser Hinrich Schütze
We present labeled morphological segmentation, an alternative view of
morphological processing that unifies several tasks. From an annotation
standpoint, we additionally introduce a new hierarchy of morphotactic tagsets.
Finally, we develop \modelname, a discriminative morphological segmentation
system that, contrary to previous work, explicitly models morphotactics. We
show that \textsc{chipmunk} yields improved performance on three tasks for all
six languages: (i) morphological segmentation, (ii) stemming and (iii)
morphological tag classification. On morphological segmentation, our method
shows absolute improvements of 2--6 points $F_1$ over the baseline.