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Evaluating LSTM models for grammatical function labelling

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...

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Hauptverfasser: Do, Bich-Ngoc (VerfasserIn) , Rehbein, Ines (VerfasserIn)
Dokumenttyp: Kapitel/Artikel Konferenzschrift
Sprache:Englisch
Veröffentlicht: September 2017
In: 15th International Conference on Parsing Technologies - proceedings of the conference
Year: 2017, Pages: 128-133
Online-Zugang:Verlag, lizenzpflichtig, Volltext: https://aclanthology.org/W17-6318
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Verfasserangaben:Bich-Ngoc Do, Ines Rehbein

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