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