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            <title>Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies</title>
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    <abstract>We present a multilingual dependency parser with a bidirectional-LSTM (BiLSTM) feature extractor and a multi-layer perceptron (MLP) classifier. We trained our transition-based projective parser in UD version 2.0 datasets without any additional data. The parser is fast, lightweight and effective on big treebanks. In the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, the official results show that the macro-averaged LAS F1 score of our system Mengest is 61.33%.</abstract>
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%0 Conference Proceedings
%T A Fast and Lightweight System for Multilingual Dependency Parsing
%A Ji, Tao
%A Wu, Yuanbin
%A Lan, Man
%Y Hajič, Jan
%Y Zeman, Dan
%S Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
%D 2017
%8 August
%I Association for Computational Linguistics
%C Vancouver, Canada
%F ji-etal-2017-fast
%X We present a multilingual dependency parser with a bidirectional-LSTM (BiLSTM) feature extractor and a multi-layer perceptron (MLP) classifier. We trained our transition-based projective parser in UD version 2.0 datasets without any additional data. The parser is fast, lightweight and effective on big treebanks. In the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, the official results show that the macro-averaged LAS F1 score of our system Mengest is 61.33%.
%R 10.18653/v1/K17-3025
%U https://aclanthology.org/K17-3025/
%U https://doi.org/10.18653/v1/K17-3025
%P 237-242

Markdown (Informal)

[A Fast and Lightweight System for Multilingual Dependency Parsing](https://aclanthology.org/K17-3025/) (Ji et al., CoNLL 2017)

• A Fast and Lightweight System for Multilingual Dependency Parsing (Ji et al., CoNLL 2017)

ACL

• Tao Ji, Yuanbin Wu, and Man Lan. 2017. A Fast and Lightweight System for Multilingual Dependency Parsing. In Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, pages 237–242, Vancouver, Canada. Association for Computational Linguistics.