Year: 2,015
Journal: Conference on Empirical Methods in Natural Language Processing
Languages: Czech, English, German, Hungarian, Latin, Spanish
Programming languages: Java
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We present LEMMING, a modular loglinear model that jointly models lemmatization and tagging and supports the integration of arbitrary global features. It is trainable on corpora annotated with gold standard tags and lemmata and does not rely on morphological dictionaries or analyzers. LEMMING sets the new state of the art in token-based statistical lemmatization on six languages

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