@inproceedings{haselbach-etal-2012-german,
title = "{G}erman \textit{nach}-Particle Verbs in Semantic Theory and Corpus Data",
author = "Haselbach, Boris and
Seeker, Wolfgang and
Eckart, Kerstin",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Do{\u{g}}an, Mehmet U{\u{g}}ur and
Maegaard, Bente and
Mariani, Joseph and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Eighth International Conference on Language Resources and Evaluation ({LREC}'12)",
month = may,
year = "2012",
address = "Istanbul, Turkey",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2012/pdf/507_Paper.pdf",
pages = "3706--3711",
abstract = "In this paper, we present a database-supported corpus study where we combine automatically obtained linguistic information from a statistical dependency parser, namely the occurrence of a dative argument, with predictions from a theory on the argument structure of German particle verbs with ''''''``nach''''''''. The theory predicts five readings of ''''''``nach'''''''' which behave differently with respect to dative licensing in their argument structure. From a huge German web corpus, we extracted sentences for a subset of ''''''``nach''''''''-particle verbs for which no dative is expected by the theory. Making use of a relational database management system, we bring together the corpus sentences and the lemmas manually annotated along the lines of the theory. We validate the theoretical predictions against the syntactic structure of the corpus sentences, which we obtained from a statistical dependency parser. We find that, in principle, the theory is borne out by the data, however, manual error analysis reveals cases for which the theory needs to be extended.",
}
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<abstract>In this paper, we present a database-supported corpus study where we combine automatically obtained linguistic information from a statistical dependency parser, namely the occurrence of a dative argument, with predictions from a theory on the argument structure of German particle verbs with ”””“nach””””. The theory predicts five readings of ”””“nach”””” which behave differently with respect to dative licensing in their argument structure. From a huge German web corpus, we extracted sentences for a subset of ”””“nach””””-particle verbs for which no dative is expected by the theory. Making use of a relational database management system, we bring together the corpus sentences and the lemmas manually annotated along the lines of the theory. We validate the theoretical predictions against the syntactic structure of the corpus sentences, which we obtained from a statistical dependency parser. We find that, in principle, the theory is borne out by the data, however, manual error analysis reveals cases for which the theory needs to be extended.</abstract>
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%0 Conference Proceedings
%T German nach-Particle Verbs in Semantic Theory and Corpus Data
%A Haselbach, Boris
%A Seeker, Wolfgang
%A Eckart, Kerstin
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Doğan, Mehmet Uğur
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC’12)
%D 2012
%8 May
%I European Language Resources Association (ELRA)
%C Istanbul, Turkey
%F haselbach-etal-2012-german
%X In this paper, we present a database-supported corpus study where we combine automatically obtained linguistic information from a statistical dependency parser, namely the occurrence of a dative argument, with predictions from a theory on the argument structure of German particle verbs with ”””“nach””””. The theory predicts five readings of ”””“nach”””” which behave differently with respect to dative licensing in their argument structure. From a huge German web corpus, we extracted sentences for a subset of ”””“nach””””-particle verbs for which no dative is expected by the theory. Making use of a relational database management system, we bring together the corpus sentences and the lemmas manually annotated along the lines of the theory. We validate the theoretical predictions against the syntactic structure of the corpus sentences, which we obtained from a statistical dependency parser. We find that, in principle, the theory is borne out by the data, however, manual error analysis reveals cases for which the theory needs to be extended.
%U http://www.lrec-conf.org/proceedings/lrec2012/pdf/507_Paper.pdf
%P 3706-3711
Markdown (Informal)
[German nach-Particle Verbs in Semantic Theory and Corpus Data](http://www.lrec-conf.org/proceedings/lrec2012/pdf/507_Paper.pdf) (Haselbach et al., LREC 2012)
ACL
- Boris Haselbach, Wolfgang Seeker, and Kerstin Eckart. 2012. German nach-Particle Verbs in Semantic Theory and Corpus Data. In Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12), pages 3706–3711, Istanbul, Turkey. European Language Resources Association (ELRA).