Preverbal syntactic complexity leads to local coherence effects

ABSTRACT

The effective use of preverbal linguistic cues to make successful clause-final verbal prediction as well as robust maintenance of such predictions has been argued to be a cross-linguistic generalisation for SOV languages such as German and Japanese. In this paper, we show that native speakers of Hindi (an SOV language) falter in forming a clause-final structure in the presence of a centre-embedded relative clause with a non-canonical word order. In particular, the fallibility of the parser is illustrated by the formation of a grammatically illicit locally coherent parse during online processing. Such a parse should not be formed if the grammatically licit matrix clause final structure was being successfully formed. The formation of a locally coherent parse is further illustrated by probing various syntactic dependencies via targeted questions. We show that the parser's susceptibility to form such structures is not driven by top-down processing, rather the effect can only be explained through a bottom-up parsing approach. Further, our investigation suggests that while plausibility is essential, presence of overt agreement features might not be necessary for forming a locally coherent parse in Hindi. These results go against top-down proposals to local coherence such as lossy surprisal and are consistent with the good-enough processing model to comprehension while only partially supporting the SOPARSE account. The work highlights how top-down processing and bottom-up information interact during sentence comprehension in SOV languages – prediction suffers with increased complexity of the preverbal linguistic environment.

KEYWORDS:

• Local coherence effect
• syntactic prediction
• good-enough processing
• sentence comprehension
• SOV languages

ABBREVIATIONS:

• SOV: Subject Object Verb
• SVO: Subject Verb Object
• RC: RelativeClause

Acknowledgments

We would like to thank Apurva, Niralee Gupta, Vasundhara Srivastava, and Srabasti Dey for their help with data collection. We also thank Shravan Vasishth and three anonymous reviewers for their comments.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 We thank an anonymous reviewer for pointing this out.

2 Recall that it is the RC verb that agrees with the object NP (see Section 2).

3 The data, analysis files and items list for this and subsequent experiments are available at the following OSF repository: https://osf.io/6rcz8/

4 Link: https://web.archive.org/web/20191220181934/http://tedlab.mit.edu/~dr/Linger/

Additional information

Funding

This work was partially supported by a Department of Science and Technology – Cognitive Science Research Initiative grant (SR/CSRI/29/2015) to Samar Husain.