BivalTyp

Лаборатория типологического изучения языков    Институт лингвистических исследований РАН

Maps

How to cite

Say, Sergey and Dmitry Nikolaev. 2021. Maps. In: Say, Sergey (ed.). BivalTyp: Typological database of bivalent verbs and their encoding frames. St. Petersburg: Institute for Linguistic Studies, RAS. (Available online at https://www.bivaltyp.info, Accessed on .)

Transitivity and locus ratio maps

These four maps display the ratios of transitive predicates and of three types of intransitive patterns in the languages of the sample. The three types of intransitive patterns are distinguished based on whether the first argument (X), the second argument (Y), or both arguments (X and Y) are encoded by oblique devices; see the section on locus in How to read the data for more detail.

Ratios of transitive predicates

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Values above 81% and below 27% have not been observed.

Ratios of predicates with the first argument (X) encoded by oblique devices

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Values above 23% have not been observed.

Ratios of predicates with the second argument (Y) encoded by oblique devices

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Values above 65% and below 16% have not been observed.

Ratios of predicates with both arguments (XY) encoded by oblique devices

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Customizable transitivity and locus map

This map shows whether translation equivalents of a given predicate (‘attack’, ‘be afraid’, etc.) belong to the transitive class in the languages of the sample. Non-transitive equivalents are further divided into three types based on their locus of intransitivity, i.e., whether the first argument (X), the second argument (Y), or both arguments are encoded by oblique devices. See How to read the data for more detail on locus.

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Customizable predicate-pair map

This map shows whether translation equivalents of two selected predicates (e.g., ‘be afraid’ and ‘avoid’) pattern together in terms of their valency class in individual languages. Note that the equivalents are considered belonging to the same valency class if and only if their first and second arguments are aligned (e.g., the classes tagged “DAT_NOM” and “NOM_DAT” in Russian are considered two different classes for the purposes of the project). See How to read the data for more detail on how language-specific valency patterns are identified.

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