Towards JointUD: Part-of-speech Tagging and Lemmatization using Recurrent Neural Networks
2018-09-10CONLL 2018Code Available0· sign in to hype
Gor Arakelyan, Karen Hambardzumyan, Hrant Khachatrian
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Abstract
This paper describes our submission to CoNLL 2018 UD Shared Task. We have extended an LSTM-based neural network designed for sequence tagging to additionally generate character-level sequences. The network was jointly trained to produce lemmas, part-of-speech tags and morphological features. Sentence segmentation, tokenization and dependency parsing were handled by UDPipe 1.2 baseline. The results demonstrate the viability of the proposed multitask architecture, although its performance still remains far from state-of-the-art.