COMBO: State-of-the-Art Morphosyntactic Analysis

• URL: http://arxiv.org/abs/2109.05361v1
• Date: Sat, 11 Sep 2021 20:00:20 GMT
• Title: COMBO: State-of-the-Art Morphosyntactic Analysis
• Authors: Mateusz Klimaszewski, Alina Wr\'oblewska
• Abstract summary: COMBO is a fully neural NLP system for accurate part-of-speech tagging, morphological analysis, lemmatisation, and (enhanced) dependency parsing. It predicts categorical morphosyntactic features whilst also exposing their vector representations, extracted from hidden layers. It is an easy to install Python package with automatically downloadable pre-trained models for over 40 languages.
• Score: 0.0
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We introduce COMBO - a fully neural NLP system for accurate part-of-speech tagging, morphological analysis, lemmatisation, and (enhanced) dependency parsing. It predicts categorical morphosyntactic features whilst also exposes their vector representations, extracted from hidden layers. COMBO is an easy to install Python package with automatically downloadable pre-trained models for over 40 languages. It maintains a balance between efficiency and quality. As it is an end-to-end system and its modules are jointly trained, its training is competitively fast. As its models are optimised for accuracy, they achieve often better prediction quality than SOTA. The COMBO library is available at: https://gitlab.clarin-pl.eu/syntactic-tools/combo.

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