Replication data for: Verbal constructional profiles: reliability, distinction power and practical applications

PID

A linguistic profile is a frequency distribution of occurrences of a linguistic item across a given parameter. Containing useful quantitative information about an item's usage, a profile can help to discover fundamental properties of the item. Here we focus on verbal constructional profiles, where the item is always a verb, and the parameter is its syntactic environment. This methodology has been used for various purposes with some success, but little is known about the basic properties of the profiles. We start by addressing two general methodological questions. First, is there such thing as a reliable constructional profile, i.e. is there a stable distribution of a verb across its syntactic contexts? If yes, what corpus size is required to capture it? Second, what distinction power do the profiles possess at different corpus sizes? To test that, we used the SynTagRus treebank of modern Russian, both in its native dependency format and converted into the PROIEL format. As a secondary goal, we compare the two dependency schemes' ability to yield useful argument structure data. We then zoom in on a more language-specific question and estimate the possibility of using verbal constructional profiles as an objective criterion in the study of Russian aspect, with a view to use it in diachronic studies. We test the method's applicability to Russian aspect, taking into account the answers we give to our methodological ques tions. We test two different hypotheses: first, that constructional profiles can be used to identify the most likely aspectual partner of a verb; second, that constructional profiles can be used to tell whether a verb is perfective or imperfective. We see that the both hypotheses hold to some extent, but only the second one seems applicable to actual research questions.

Identifier
PID https://hdl.handle.net/10037.1/10142
Related Identifier https://hdl.handle.net/10037.1/10142
Metadata Access https://dataverse.no/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=hdl:10037.1/10142
Provenance
Creator Berdicevskis, Aleksandrs;Eckhoff, Hanne
Publisher DataverseNO
Publication Year 2018
Representation
Resource Type corpus
Coverage
Discipline Humanities