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

2.4 The RC Extraction Preference in Mandarin
Theory E-S C-S C-O
√ √
Canonicity
√ √
IC
√ √
SC + Gap
√ √
Accessibility
√ √
Expectation
√ √
Perspective
√ √
RC Frequency
√
Active Filler
? ?
SC + Elided Subj. √ ( √ )
√ √ √
Experience
( ) ( )
Table 2.3: Extraction preference predictions for English and Mandarin RCs. E-S =
English subject preference. C-S and C-O = Chinese subject or object preference,
respectively. IC = Integration Cost, SC = Storage Cost.
doubly embedded RCs show an object preference. According to Lin (2007) a garden
path effect is expected in both RC types due to an initial misinterpretation as a main
clause. A reanalysis should take place at the relativizer/head noun region, especially in
the ORC, leading to higher reading times. Interestingly, Hsiao and Gibson’s data do not
show such an effect. Nevertheless, Hsiao and Gibson argue for an initial misanalysis in
the ORC but not in the SRC. Under these premises their result is consistent with the
Storage Cost account when interpreted in terms of the Gap Assumption: In the SRC
more heads are predicted, since an RC is expected, while in the ORC according to a
main clause interpretation less heads are predicted. Hsiao and Gibson assume that no
reanalysis is necessary because the already constructed main clause structure in the ORC
does not have to be modified for attaching it as a relative clause. Concerning Integration
Cost, the results do not support the theory. As there is no significant effect on the head
noun, the results do not show the predicted Integration Cost due to a longer filler-gap
distance in the SRC. A naive application of the canonicity account would definitely fit
the data. The more canonical ORC structure, which resembles the main clause word
order, seems indeed easier to process. However, as Hsiao and Gibson state themselves,
it remains unclear what canonicity and structural frequency accounts predict without
having reasonable evidence for what counts as canonical or what structural level feeds
into frequency calculations.
There are five major issues in Hsiao and Gibson’s study that can be criticized.
a) Animacy Hsiao and Gibson only used animate NPs in their stimuli. Kuo and
Vasishth’s corpus study (reported in 2.2) revealed that hardly any RC-like structures
actually contain two animate NPs. In cases with an animate embedded noun the most
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