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Alternating constructions with ditransitive geben in present-day German

  • Hilde De Vaere

    Hilde De Vaere (born 1957) is a doctoral researcher at the Department of Linguistics at Ghent University. Her research focuses on the syntax–semantics interface, in particular the corpus-based study of alternating syntactic constructions with ditransitive verbs in present-day German.

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    , Ludovic De Cuypere

    Ludovic De Cuypere (born 1978, PhD Ghent University, 2007) currently combines a position as a teaching assistant at the Department of Linguistics at Ghent University, where he teaches statistics and provides statistical consultancy, with a part-time professorship at the Department of Linguistics and Literary Studies at the Vrije Universiteit Brussel, where he teaches courses on English Linguistics and Research Methodology. His PhD dissertation dealt with the iconicity hypothesis in language. His research focuses on alternating syntactic constructions from multiple perspectives.

    and Klaas Willems

    Klaas Willems (born 1965, PhD Ghent University, 1992) is a professor in General Linguistics at the Department of Linguistics at Ghent University. His main research interests are in the theory of language (including semiotics and the history of linguistics), the theory of semantics, and German grammar (with a focus on the syntax-semantics interface). Address: Department of linguistics, University of Gent, Blandijnberg 2, B-9000 Gent (Belgium).

Published/Copyright: May 25, 2018

Abstract

This paper reports on a corpus-based investigation of the verb geben in two alternating ditransitive constructions in present-day German with the Recipient either coded in the dative case (the indirect object construction, abbreviated: IOC) or by means of the PP an + accusative case (the prepositional object construction, POC). The study is based on a quantitative analysis of N=1,301 sentences (712 IOC and 589 POC) drawn from the Deutsche Referenzkorpus (IDS, Mannheim) which were annotated for 20 factors. Using a logistic regression analysis, we found evidence for the effect of 10 predictors (bootstrapped C-index=95%). We discuss our results in comparison to corpus-based research of the English dative alternation and point to some notable differences between both languages. In German, POC appears to be strongly correlated with collective recipients, collective agents, passive voice, and concrete and propositional transfer senses of the main verb geben. With regard to the semantics of geben, we argue that the quantitative findings are best accounted for on the basis of a general underspecified verb meaning ‘geben transfer’ that does not yet differentiate between the three possible verb senses (concrete, abstract, and propositional).

About the authors

Hilde De Vaere

Hilde De Vaere (born 1957) is a doctoral researcher at the Department of Linguistics at Ghent University. Her research focuses on the syntax–semantics interface, in particular the corpus-based study of alternating syntactic constructions with ditransitive verbs in present-day German.

Ludovic De Cuypere

Ludovic De Cuypere (born 1978, PhD Ghent University, 2007) currently combines a position as a teaching assistant at the Department of Linguistics at Ghent University, where he teaches statistics and provides statistical consultancy, with a part-time professorship at the Department of Linguistics and Literary Studies at the Vrije Universiteit Brussel, where he teaches courses on English Linguistics and Research Methodology. His PhD dissertation dealt with the iconicity hypothesis in language. His research focuses on alternating syntactic constructions from multiple perspectives.

Klaas Willems

Klaas Willems (born 1965, PhD Ghent University, 1992) is a professor in General Linguistics at the Department of Linguistics at Ghent University. His main research interests are in the theory of language (including semiotics and the history of linguistics), the theory of semantics, and German grammar (with a focus on the syntax-semantics interface). Address: Department of linguistics, University of Gent, Blandijnberg 2, B-9000 Gent (Belgium).

Acknowledgements

We would like to thank two anonymous reviewers for providing helpful suggestions and comments on an earlier version of this article.

Appendix

A Appendix A Logistic Regression Model

lrm(formula=Construction ~ Voice + TransferSense + AgentAnim +

Metaphor + ThemePron + ThemeGiv + ThemeAnim + ThemeConc +

ThemeDef + ThemeIdiom + RecPron + RecGiv + RecAnim + RecConc +

RecDef + RecNum + RecProper + rcs(LengthDiff), data=geben,

x=TRUE, y=TRUE, penalty=0.89)

Penalty factors

simple nonlinear interaction nonlinear.interaction
0.89 0.89 0.89 0.89
Model Likelihood Discrimination Rank Discrim.
Ratio Test Indexes Indexes
Obs 1268 LR chi2 1093.11 R2 0.763 C 0.958
IOC(r-t) 680 d.f. 24.69 g 4.172 Dxy 0.916
POC(t-r) 588 Pr(>chi2) <0.0001 gr 64.823 gamma 0.917
max |deriv| 1e-11 Penalty 20.16 gp 0.451 tau-a 0.456
Brier 0.080
Coef S.E. Wald Z Pr(>|Z|) Penalty Scale
Intercept −0.3414 1.2992 –0.26 0.7927 0.0000
Voice=passive 1.9130 0.5833 3.28 0.0010 0.6671
TransferSense=concrete 1.6035 0.4469 3.59 0.0003 0.7703
TransferSense=propositional 1.6587 0.6361 2.61 0.0091 0.7703
AgentAnim=inanimate −1.6615 0.4635 –3.59 0.0003 0.8170
AgentAnim=individual −0.8272 0.2408 –3.44 0.0006 0.8170
AgentAnim=notexpressed −0.7213 0.5343 –1.35 0.1770 0.8170
Metaphor=yes −0.6328 0.5373 –1.18 0.2389 0.6671
ThemePron=pronominal 1.1075 0.5829 1.90 0.0574 0.6671
ThemeGiv=given 0.2858 0.2889 0.99 0.3225 0.7703
ThemeGiv=new −1.0374 0.2513 –4.13 <0.0001 0.7703
ThemeAnim=inanimate −0.1903 0.7760 –0.25 0.8062 0.6671
ThemeConc=concrete 2.4817 0.4569 5.43 <0.0001 0.7703
ThemeConc=propositional 2.2824 0.6575 3.47 0.0005 0.7703
ThemeDef=indefinite −0.2533 0.2158 –1.17 0.2405 0.6671
ThemeIdiom=yes −1.8423 0.9112 –2.02 0.0432 0.6671
RecPron=pronominal −0.9878 0.3299 –2.99 0.0028 0.6671
RecGiv=given −1.2010 0.2776 –4.33 <0.0001 0.7703
RecGiv=new 0.3527 0.2949 1.20 0.2317 0.7703
RecAnim=individual −1.2652 0.2611 –4.84 <0.0001 0.8170
RecAnim=inanimate −2.9904 0.4443 –6.73 <0.0001 0.8170
RecAnim=underspecified 0.4014 0.2900 1.38 0.1663 0.8170
RecConc=concrete 0.0391 0.8356 0.05 0.9627 0.6671
RecDef=indefinite −0.0249 0.3426 –0.07 0.9421 0.6671
RecNum=singular 0.4466 0.2278 1.96 0.0500 0.6671
RecProper=proper −0.6114 0.3372 –1.81 0.0698 0.6671
LengthDiff 0.2242 0.0609 3.68 0.0002 4.3937
LengthDiff’ −0.0246 0.1203 –0.20 0.8381 4.4114
LengthDiff’’ −0.8149 0.9720 –0.84 0.4018 0.4059

B Sample probabilities

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The online version of this article offers supplementary material (https://doi.org/10.1515/cllt-2017-0072).


Published Online: 2018-05-25
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