Improved unsupervised POS induction through prototype discovery

Authors:
Omri Abend;Roi Reichart;Ari Rappoport
Affiliations:
Hebrew University of Jerusalem;Hebrew University of Jerusalem;Hebrew University of Jerusalem
Venue:
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Year:
2010

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Abstract

We present a novel fully unsupervised algorithm for POS induction from plain text, motivated by the cognitive notion of prototypes. The algorithm first identifies landmark clusters of words, serving as the cores of the induced POS categories. The rest of the words are subsequently mapped to these clusters. We utilize morphological and distributional representations computed in a fully unsupervised manner. We evaluate our algorithm on English and German, achieving the best reported results for this task.