@inproceedings{broscheit-etal-2010-extending,
title = "Extending {BART} to Provide a Coreference Resolution System for {G}erman",
author = "Broscheit, Samuel and
Ponzetto, Simone Paolo and
Versley, Yannick and
Poesio, Massimo",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Piperidis, Stelios and
Rosner, Mike and
Tapias, Daniel",
booktitle = "Proceedings of the Seventh International Conference on Language Resources and Evaluation ({LREC}'10)",
month = may,
year = "2010",
address = "Valletta, Malta",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2010/pdf/500_Paper.pdf",
abstract = "We present a flexible toolkit-based approach to automatic coreference resolution on German text. We start with our previous work aimed at reimplementing the system from Soon et al. (2001) for English, and extend it to duplicate a version of the state-of-the-art proposal from Klenner and Ailloud (2009). Evaluation performed on a benchmarking dataset, namely the TueBa-D/Z corpus (Hinrichs et al., 2005b), shows that machine learning based coreference resolution can be robustly performed in a language other than English.",
}
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%0 Conference Proceedings
%T Extending BART to Provide a Coreference Resolution System for German
%A Broscheit, Samuel
%A Ponzetto, Simone Paolo
%A Versley, Yannick
%A Poesio, Massimo
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Piperidis, Stelios
%Y Rosner, Mike
%Y Tapias, Daniel
%S Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC’10)
%D 2010
%8 May
%I European Language Resources Association (ELRA)
%C Valletta, Malta
%F broscheit-etal-2010-extending
%X We present a flexible toolkit-based approach to automatic coreference resolution on German text. We start with our previous work aimed at reimplementing the system from Soon et al. (2001) for English, and extend it to duplicate a version of the state-of-the-art proposal from Klenner and Ailloud (2009). Evaluation performed on a benchmarking dataset, namely the TueBa-D/Z corpus (Hinrichs et al., 2005b), shows that machine learning based coreference resolution can be robustly performed in a language other than English.
%U http://www.lrec-conf.org/proceedings/lrec2010/pdf/500_Paper.pdf
Markdown (Informal)
[Extending BART to Provide a Coreference Resolution System for German](http://www.lrec-conf.org/proceedings/lrec2010/pdf/500_Paper.pdf) (Broscheit et al., LREC 2010)
ACL