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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 11 of 11 1 Evaluating a Dependency Parser on DeReKo Fankhauser, Peter [Verfasser]; Do, Bich-Ngoc [Verfasser]; Kupietz, Marc [Verfasser]. - Mannheim : Leibniz-Institut für Deutsche Sprache (IDS), Bibliothek, 2020 DNB Subject Category Language Show details 2 Parsers Know Best: German PP Attachment Revisited ... The 28th International Conference on Computational Linguistics 2020; Do, Bich-Ngoc; Rehbein, Ines. - : Underline Science Inc., 2020 BASE Show details 3 Neural reranking for dependency parsing: An evaluation Do, Bich-Ngoc; Rehbein, Ines. - : Association for Computational Linguistics, ACL, 2020 Abstract: Recent work has shown that neural rerankers can improve results for dependency parsing over the top k trees produced by a base parser. However, all neural rerankers so far have been evaluated on English and Chinese only, both languages with a configurational word order and poor morphology. In the paper, we re-assess the potential of successful neural reranking models from the literature on English and on two morphologically rich(er) languages, German and Czech. In addition, we introduce a new variation of a discriminative reranker based on graph convolutional networks (GCNs). We show that the GCN not only outperforms previous models on English but is the only model that is able to improve results over the baselines on German and Czech. We explain the differences in reranking performance based on an analysis of a) the gold tree ratio and b) the variety in the k-best lists. Keyword: 004 Informatik URL: https://madoc.bib.uni-mannheim.de/55426 https://madoc.bib.uni-mannheim.de/55426/ https://madoc.bib.uni-mannheim.de/55426/1/2020.acl-main.379-1.pdf BASE Hide details 4 Parsers know best: German PP attachment revisited Do, Bich-Ngoc; Rehbein, Ines. - : ACM Digital Library, 2020 BASE Show details 5 Evaluating LSTM models for grammatical function labelling Do, Bich-Ngoc [Verfasser]; Rehbein, Ines [Verfasser]. - Mannheim : Institut für Deutsche Sprache, Bibliothek, 2017 DNB Subject Category Language Show details 6 What do we need to know about an unknown word when parsing German Do, Bich-Ngoc [Verfasser]; Rehbein, Ines [Verfasser]; Frank, Anette [Verfasser]. - Mannheim : Institut für Deutsche Sprache, Bibliothek, 2017 DNB Subject Category Language Show details 7 Universal Dependencies are hard to parse – or are they? Rehbein, Ines [Verfasser]; Steen, Julius [Verfasser]; Do, Bich-Ngoc [Verfasser]. - Mannheim : Institut für Deutsche Sprache, Bibliothek, 2017 DNB Subject Category Language Show details 8 What do we need to know about an unknown word when parsing German [Online resource] Do, Bich-Ngoc; Rehbein, Ines; Frank, Anette IDS-Repository Show details 9 Universal Dependencies are hard to parse – or are they? [Online resource] Rehbein, Ines; Steen, Julius; Do, Bich-Ngoc. IDS-Repository Show details 10 Evaluating LSTM models for grammatical function labelling [Online resource] Do, Bich-Ngoc; Rehbein, Ines IDS-Repository Show details 11 Evaluating a Dependency Parser on DeReKo [Online resource] Fankhauser, Peter; Do, Bich-Ngoc; Kupietz, Marc IDS-Repository Show details

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