Connectionist Modeling of Experience-based Effects in Sentence ...

4.3 RC Extraction in Mandarin
Results
Figure 4.5 shows the GPE scores by region and epoch for SRCs and ORCs. Table
A.2 (in the appendix) shows means and standard error for the first two regions. The
improvement on the main verb in the ORC over epochs was comparably low. There was
no improvement on the SRC main verb. The training improvement on the relativizer
in SRC happened predominantly between the first and the second epoch. An object
advantage on the relativizer was only present in the first and slightly in the second epoch.
The third epoch did not reveal an ORC advantage. In addition a subject preference was
found on the pre-relativizer region in the second and third epoch (P < 0.001).
GPE
0.0 0.2 0.4 0.6 0.8 1.0
Mandarin SRC (85%)
N1 de N2 V2 N3
Region
epoch 1
epoch 2
epoch 3
GPE
0.0 0.2 0.4 0.6 0.8 1.0
Mandarin ORC (25%)
V1 de N2 V2 N3
Region
Figure 4.5: Simulation 2: Mandarin SRC Frequency
epoch 1
epoch 2
epoch 3
The heavily improved predictions for the relativizer in the SRC imply an increased
familiarity effect due to the corpus containing more SRCs than before. The result of
simulation 2 suggests that the regularity effect on object relatives is weak and can easily
be affected by a slight distributional disproportion in favor of the SRC structure.
4.3.3 Discussion
Simulation 1 confirms the regularity advantage for Mandarin ORCs with respect to
simple sentences with the greatest effect on the relativizer. However, the location of the
effect is not consistent with human data. Recall that Hsiao and Gibson (2003) found an
object preference on the pre-relativizer region whereas Kuo and Vasishth (2007) found a
subject preference on the relativizer and the head noun. Besides the very small effect on
N1/V1 in the simulation there is no region-specific consistency with empirical studies.
71