LemmaTag: Jointly Tagging and Lemmatizing for Morphologically Rich Languages with BRNNs
2018-10-01EMNLP 2018Code Available0· sign in to hype
Daniel Kondratyuk, Tom{\'a}{\v{s}} Gaven{\v{c}}iak, Milan Straka, Jan Haji{\v{c}}
Code Available — Be the first to reproduce this paper.
ReproduceCode
- github.com/hyperparticle/LemmaTagOfficialIn papertf★ 0
Abstract
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.