The connection between part-of-speech (POS) categories and morphological properties is well-documented in linguistics but underutilized in text processing systems. This paper proposes a novel model for morphological segmentation that is driven by this connection. Our model learns that words with common affixes are likely to be in the same syntactic category and uses learned syntactic categories to refine the segmentation boundaries of words. Our results demonstrate that incorporating POS categorization yields substantial performance gains on morphological segmentation of Arabic.
Lee et al. REF address the connection between syntax and morphology in a statistical model.
Modeling Syntactic Context Improves Morphological Segmentation
Proceedings of the Fifteenth Conference on Computational Natural Language Learning
Computer Science