LemmaTag: Jointly Tagging and Lemmatizing for Morphologically-Rich Languages with BRNNs release_ujvw6dc7zbdw7p7kcypanmrja4

by Daniel Kondratyuk, Tomáš Gavenčiak, Milan Straka, Jan Hajič

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We present LemmaTag, a featureless neural network architecture that jointly generates part-of-speech tags and lemmas for sentences by using bidirectional RNNs with character-level and word-level embeddings. We demonstrate that both tasks benefit from sharing the encoding part of the network, predicting tag subcategories, and using the tagger output as an input to the lemmatizer. We evaluate our model across several languages with complex morphology, which surpasses state-of-the-art accuracy in both part-of-speech tagging and lemmatization in Czech, German, and Arabic.
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Type  article
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Date   2018-08-27
Version   v2
Language   en ?
arXiv  1808.03703v2
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