Connectionist Modeling of Experience-based Effects in Sentence ...
Connectionist Modeling of Experience-based Effects in Sentence ...
Connectionist Modeling of Experience-based Effects in Sentence ...
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Chapter 2 Issues <strong>in</strong> Relative Clause Process<strong>in</strong>g<br />
center on the RC object which is the only NP available, wrongly <strong>in</strong>terpret<strong>in</strong>g it as an<br />
object? If so, read<strong>in</strong>g an SRC would also require one shift, namely from the embedded<br />
NP to the sentential subject. This makes SRCs numerically as hard as ORCs. In addition<br />
to the perspective shift <strong>in</strong> the SRC a reanalysis would be expected. The answers to the<br />
questions concern<strong>in</strong>g perspective shift <strong>in</strong> Ch<strong>in</strong>ese depends on the mechanism guid<strong>in</strong>g the<br />
reader’s perspective when subject is ambiguous or absent. To sum up, the perspective<br />
shift account could probably account for a subject advantage <strong>in</strong> Mandar<strong>in</strong>, but this is<br />
not clear. If so, an effect is expected on the head noun.<br />
2.3.6 Summary<br />
Table 2.3 shows an overview <strong>of</strong> the theories addressed here and their predictions regard<strong>in</strong>g<br />
English and Mandar<strong>in</strong> RCs. All mentioned theories agree on a subject preference<br />
for English. However, a heterogenous picture appears on the Mandar<strong>in</strong> side. There<br />
is a slight bias <strong>in</strong> the prediction pattern <strong>in</strong> favor <strong>of</strong> a subject preference. This would<br />
<strong>in</strong>tegrate nicely <strong>in</strong>to an otherwise universal consistency. Accessibility, Expectation, perspective<br />
shift, and pure RC type frequency predict a clear subject preference, whereas<br />
canonicity, Integration Cost, and Storage Cost under the Gap Assumption predict an<br />
ORC advantage. Storage Cost under the Elided Subject Assumption would predict a<br />
subject advantage on the RC region and an object advantage on the head noun. The<br />
predictions <strong>of</strong> the Active Filler Strategy are unclear. As for experience, due to the granularity<br />
problem the predictions are not clear. A connectionist implementation, as follows<br />
<strong>in</strong> chapter 4, is believed to make more specific predictions. Anticipat<strong>in</strong>g the results, the<br />
simulations predicted a weak ORC preference, which appeared, however, only at the<br />
relativizer. Account<strong>in</strong>g for the corpus data by Kuo and Vasishth (2007) even caused<br />
a subject preference <strong>in</strong> the RC region. To f<strong>in</strong>d out about the just discussed theories’<br />
compatibility with empirical data, the next section will report important studies on the<br />
subject/object difference <strong>in</strong> Ch<strong>in</strong>ese.<br />
2.4 The RC Extraction Preference <strong>in</strong> Mandar<strong>in</strong><br />
Hsiao and Gibson, 2003<br />
The self-paced read<strong>in</strong>g study by Hsiao and Gibson (2003) was the first to report results<br />
address<strong>in</strong>g the subject/object difference <strong>in</strong> Ch<strong>in</strong>ese. It had great impact on the discussion<br />
about the universality <strong>of</strong> the subject preference across-languages because Ch<strong>in</strong>ese<br />
was the first exception discovered. Hsiao and Gibson studied s<strong>in</strong>gly and doubly embedded<br />
Mandar<strong>in</strong> relative clauses like the ones <strong>in</strong> examples (2.2) and (10) <strong>in</strong> a self-paced<br />
read<strong>in</strong>g task. For s<strong>in</strong>gle-embedd<strong>in</strong>g they found an advantage for ORCs on the region<br />
before the relativizer (N1 V1 / V1 N1). For the double-embedded RCs the relevant<br />
regions were the 3rd and 4th word (de1 N2 / N1 de1 ) and the 5th and 6th word (V2<br />
de2 / N2 de2 ). On both regions an object advantage was measured. Both s<strong>in</strong>gly and<br />
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