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In this work, we propose an algorithm that induces morphological networks for Persian and Turkish. The algorithm uses morpheme-segmented lexicons for the two languages. The resulting networks capture both derivational and inflectional relations. The network induction algorithm can use either manually annotated lists of roots and affixes, or simple heuristics to distinguish roots from affixes. We evaluate both variants empirically. We use our large handsegmented set of word forms in the experiments with Persian, which is contrasted with employing only a very limited manually segmented lexicon for Turkish that existed previously. The network-induction algorithm uses gold segmentation data for initializing the networks, which are subsequently extended with additional corpus-attested word forms that were unseen in the segmented data. For this purpose, we use existing morpheme-segmentation tools, namely supervised and unsupervised version of Morfessor, and (unsupervised) MorphSyn. The experimental results show that the accuracy of segmented initial data influences derivational network quality.

Morphological Networks for Persian and Turkish: What Can Be Induced from Morpheme Segmentation?