Labeled Morphological Segmentation with Semi-Markov Models
CoNLL(2024)
摘要
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 , a discriminative morphological segmentation
system that, contrary to previous work, explicitly models morphotactics. We
show that 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.
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