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        <title>Evaluating LSTM models for grammatical function labelling</title>
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            <title>Proceedings of the 15th International Conference on Parsing Technologies</title>
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            <namePart type="given">Yusuke</namePart>
            <namePart type="family">Miyao</namePart>
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            <namePart type="given">Kenji</namePart>
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    <abstract>To improve grammatical function labelling for German, we augment the labelling component of a neural dependency parser with a decision history. We present different ways to encode the history, using different LSTM architectures, and show that our models yield significant improvements, resulting in a LAS for German that is close to the best result from the SPMRL 2014 shared task (without the reranker).</abstract>
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%0 Conference Proceedings
%T Evaluating LSTM models for grammatical function labelling
%A Do, Bich-Ngoc
%A Rehbein, Ines
%Y Miyao, Yusuke
%Y Sagae, Kenji
%S Proceedings of the 15th International Conference on Parsing Technologies
%D 2017
%8 September
%I Association for Computational Linguistics
%C Pisa, Italy
%F do-rehbein-2017-evaluating
%X To improve grammatical function labelling for German, we augment the labelling component of a neural dependency parser with a decision history. We present different ways to encode the history, using different LSTM architectures, and show that our models yield significant improvements, resulting in a LAS for German that is close to the best result from the SPMRL 2014 shared task (without the reranker).
%U https://aclanthology.org/W17-6318
%P 128-133

Markdown (Informal)

[Evaluating LSTM models for grammatical function labelling](https://aclanthology.org/W17-6318) (Do & Rehbein, IWPT 2017)

• Evaluating LSTM models for grammatical function labelling (Do & Rehbein, IWPT 2017)

ACL

• Bich-Ngoc Do and Ines Rehbein. 2017. Evaluating LSTM models for grammatical function labelling. In Proceedings of the 15th International Conference on Parsing Technologies, pages 128–133, Pisa, Italy. Association for Computational Linguistics.