List of tables :

Part of

The Ditransitive Alternation in Present-Day German: A corpus-based analysis
Hilde De Vaere
[Studies in Germanic Linguistics 6] 2023
► pp. xiii–xv

List of tables

Table 1.Verb classes according to Starke, Matzel and Duden

Table 2.Pinker’s nine semantic verb classes vs. Levin’s alternating verbs and Goldberg’s related senses of the Ditransitive Construction

Table 3.Summary of the terminology at the semantics/pragmatics interface

Table 4.Overall frequency of the noncomplex verbs under study and their relative frequency in an explicit intransitive, monotransitive and ditransitive syntax measured by means of random samples

Table 5.Complex verbs that barely alternate

Table 6.Overall frequency of the complex verbs under study and their relative frequency in an explicit intransitive, monotransitive and ditransitive syntax measured by means of random samples

Table 7.Ditransitive realisations of schicken and senden based on 4 random samples of 100 attestations each

Table 8.Proportions IOC/POC in the schicken/senden dataset

Table 9.Proportions IOC/POC per complex -geben verb

Table 10.Proportions IOC/POC per complex -schicken/senden verb

Table 11.Proportions IOC/POC per complex verb for ausleihen, verkaufen and verleihen

Table 12.Variable annotation in the different datasets

Table 13.Senses in the complex dataset: DWDS sense

Table 14.IOC/POC proportions in the geben dataset

Table 15.Proportions of the ditransitive uses of geben

Table 16.Constituent order in the geben dataset

Table 17.The geben model

Table 18.Proportions according to the random samples

Table 19.Proportions of ditransitive uses of schicken and senden

Table 20.Constituent order in the schicken and senden dataset

Table 21.Association between constituent order and alternant in the schicken and senden dataset

Table 22.The schicken/senden model

Table 23.Confusion matrix for schicken. Correct within sample prediction rate = 83%

Table 24.Confusion matrix for senden. Correct within sample prediction rate = 78%

Table 25.Bivariate sample distribution between schicken and senden vs. IOC, an-POC and zu-POC

Table 26.Confusion matrix for schicken and senden. Correct within sample prediction rate = 81%

Table 27.Bivariate frequencies and proportions (verb by Cx and constituent order) in the complex -geben dataset

Table 28.The complex geben ANOVA

Table 29.The complex geben model

Table 30.Confusion matrix for abgeben. Correct within sample prediction rate = 85%

Table 31.Confusion matrix for preisgeben. Correct within sample prediction rate = 80%

Table 32.Abstract-concrete continuum observed in preisgeben

Table 33.Confusion matrix for übergeben. Correct within sample prediction rate = 69%

Table 34.Confusion matrix for zurückgeben. Correct within sample prediction rate = 78%

Table 35.Confusion matrix for weitergeben. Correct within sample prediction rate = 88%

Table 36.Bivariate frequencies and proportions (verb by Cx and constituent order) in the complex -schicken/senden dataset

Table 37.The complex schicken/senden model

Table 38.Confusion matrix for the complex -schicken/senden verbs. Correct within sample prediction rate = 86%

Table 39.Confusion matrix for einschicken. Correct within sample prediction rate = 88%

Table 40.Confusion matrix for einschicken. Correct within sample prediction rate = 84%

Table 41.Confusion matrix for zurückschicken. Correct within sample prediction rate = 87%

Table 42.Confusion matrix for zurücksenden. Correct within sample prediction rate = 82.5%

Table 43.Confusion matrix for übersenden. Correct within sample prediction rate = 79%

Table 44.Confusion matrix for weiterschicken. Correct within sample prediction rate = 95%

Table 45.Bivariate frequencies and proportions (verb by Cx and constituent order) in the ausleihen, verleihen, verkaufen dataset

Table 46.The ausleihen, verleihen, verkaufen model

Table 47.Confusion matrix for ausleihen, verleihen and verkaufen. Correct within sample prediction rate = 90%

Table 48.Confusion matrix for ausleihen. Correct within sample prediction rate = 94%

Table 49.Confusion matrix for verleihen. Correct within sample prediction rate = 95%

Table 50.Confusion matrix for verkaufen. Correct within sample prediction rate = 85%

Table 51.Motivating factors in the five datasets according to the logistic regression analyses

Table 52.Splitting points in the CITs for schicken, senden, the -geben complex and the -schicken/senden complex verbs

Table 53.Splitting points in the CITs for ausleihen, verleihen and verkaufen

Table 54.Hierarchy of the semantic features according to Wegener (1985: 322)

Table 55.The goal argument in the schicken dataset

Table 56.The goal argument in the senden dataset

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