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MD5: b675d8983ebbadceccba4682d81b32f0
This file contains the necessary info about the data and the files in this data package. |
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MD5: f8c075963a1b0d8e278725127d5e3b07
This file contains the annotated sample of 200 relevant examples of the verb mulțumi ‘thank' |
Adobe PDF - 59.4 KB -
MD5: 2f2a6f31b71170148627307b4c6b0cab
This file contains info about the annotated variables, their levels and extra explanations |
Comma Separated Values - 64.9 KB -
MD5: 319ee2bb82790089c6c272a338f71656
This file contains the annotated sample of 200 relevant examples of the verb plăcea ‘like’ |
Adobe PDF - 58.6 KB -
MD5: e02588c2bc90ad8a6711ac9158f0b067
This file contains info about the annotated variables, their levels and extra explanations |
Adobe PDF - 70.0 KB -
MD5: eb0f11668f0dbe7cce4b6d73cfed463e
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Adobe PDF - 43.6 KB -
MD5: a28593195f438e5f7c636188021fb053
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Adobe PDF - 46.0 KB -
MD5: 00b3c2c74d2b64adf3e973de070879ee
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Sep 3, 2025
Zhang, Liulin, 2025, "Replication data for: Measure schematicity through information content: A quantitative approach to grammaticalization", https://doi.org/10.18710/APTUHA, DataverseNO, V1
This is a study to propose a quantitative method to compute the schematicity of constructions, which is a key indicator of the level of grammaticalization of morphemes. In this method, to estimate the schematicity of a schema made up of two morphemes, i.e., X_ (X is the target morpheme and _ represents an open slot), we need to know the total token... |
Sep 3, 2025 -
Replication data for: Measure schematicity through information content: A quantitative approach to grammaticalization
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MD5: 6024abade0c3d2c1ff18d7ab76861e7f
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