Publications
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Do, B.-N. and Rehbein, I. (2020):
Parsers Know Best: German PP Attachment
Revisited. Proceedings of the 28th International Conference on
Computational Linguistics (COLING 2020), Barcelona, Spain (Online), pp.
2049--2061, International Committee on Computational Linguistics.
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Do, B.-N. and Rehbein, I. (2020):
Neural Reranking for Dependency Parsing: An
Evaluation. Proceedings of the 58th Annual Meeting of the Association
for Computational Linguistics (ACL 2020), Online, pp. 4123--4133,
Association for Computational Linguistics.
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Fankhauser, P., Do, B.-N., and Kupietz, M. (2020):
Evaluating a Dependency
Parser on DeReKo. Proceedings of the 8th Workshop on the Challenges in
the Management of Large Corpora (CMLC-8), Marseille, France, pp. 10--14.
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Rehbein, I., Ruppenhofer, J., and Do, B.-N. (2019):
tweeDe - A Universal
Dependencies Treebank for German Tweets. Proceedings of the 18th
International Workshop on Treebanks and Linguistic Theories (TLT, SyntaxFest
2019), Paris, France, pp. 100--108.
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Do, B.-N., Rehbein, I., and Frank, A. (2017):
What Do We Need to Know about an
Unknown Word When Parsing German. Proceedings of the 1st Workshop on
Subword and Character Level Models in NLP (SCLeM 2017), Copenhagen,
Denmark, September, pp. 117--123.
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Do, B.-N. and Rehbein, I. (2017):
Evaluating LSTM Models for Grammatical
Function Labelling. Proceedings of the 15th International Conference on
Parsing Technologies (IWPT 2017), Pisa, Italy, September, pp. 128--133.
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Rehbein, I., Steen, J., Do, B.-N., and Frank, A. (2017):
Universal Dependencies
are Hard to Parse - or are They? Proceedings of the International
Conference on Dependency Linguistics (Depling 2017), Pisa, Italy,
September, pp. 218--228.
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