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

2.3 Predicting RC Extraction Preferences Cross-linguistically
SRC provides further evidence for the elided subject assumption favored by Kuo and
Vasishth (2007).
How are the special characteristics of the Mandarin RC involved in processing differences
between subject and object extraction? Do they lead to a subject preference
prediction or do they account for a deviance from a cross-linguistically consistent theory?
What further properties of Chinese Mandarin have to be taken into account to gain
useful predictions? I will now briefly resume the theories concerning the subject/object
difference that were presented in chapter 1 and make their predictions for Mandarin and
English relative clauses explicit. Then, empirical studies concerning the Mandarin RCs
will be examined and related to the theoretical predictions.
2.3 Predicting RC Extraction Preferences
Cross-linguistically
2.3.1 Memory
DLT
In the SRC in examples (1a) and (8a) the distance between the filler (the head noun)
and its gap is short. The ORC (examples 1b and 8b) on the other hand, contains a
distant dependency. The cost metrics as illustrated for English in figure 2.2 show that
the Dependency Locality Theory accounts for higher difficulties in the ORC.
SRC The reporter whoi ei attacked the senator admitted the error
C(I) 0 0 0 0+1 0 0+1 3 0 0+1
C(S) 2 1 3 2 2 1 1 1 0
Total 2 1 3 3 2 2 4 1 1
ORC The reporter whoi the senator attacked ei admitted the error
C(I) 0 0 0 0 0 1+2 3 0 0+1
C(S) 2 1 3 4 3 1 1 1 0
Total 2 1 3 4 3 3 4 1 1
Figure 2.2: DLT cost metrics for English object and subject relative clauses
The example shows that Integration Cost on the embedded verb attacked is higher
for the ORC because two integrations take place at that position. First, attacked is
integrated with its subject senator, consuming 1 EU. Establishing the relation between
the relative pronoun who and the empty element consumes 2 EU because two discourse
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