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Syntactic representation is independent of semantics in Mandarin: evidence from syntactic priming

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Pages 211-220 | Received 29 Apr 2018, Accepted 05 Jul 2019, Published online: 18 Jul 2019
 

ABSTRACT

Theories of language processing generally assume that speakers construct independent representations for syntactic and semantic information, based largely on evidence from English and related languages. But it is not clear whether the assumption of autonomous syntactic representations extends to other languages with different typological characteristics. We therefore conducted two structural priming studies investigating production of dative sentences in Mandarin, a language whose interpretation appears to be more reliant on non-relational (intrinsic) semantics (e.g. animacy features). We examined whether participants’ tendency to repeat syntax was affected by whether the theme and recipient arguments matched or mismatched in animacy across prime and target. Participants repeated syntax to the same extent irrespective of whether prime and target arguments had matched or mismatched animacy. These findings provide evidence that the separation of syntactic and semantic representations occurs in Mandarin and therefore may occur across languages.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes

1 In a small number of items, the inanimate noun could also be interpreted with a non-recipient role, e.g. location.

2 The fact that priming occurred to the same extent following PO and PO-AR primes also indicates that any relational semantic differences between the PO and PO-AR primes (see note i) did not contribute to priming, and hence that the primed representations did not involve relational semantic information.

Additional information

Funding

The research was supported by the National Science Foundation of China under [grant number 31500880]; Royal Society of Edinburgh; National Social Science Foundation of China under [grant number 15AZD048], and  Guangzhou Philosophy and Social Science Foundation under [grant number 2018GZYB40].

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