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Plain Text - 19.2 KB - MD5: d6b2e91b351a27929128d10599e1e468
Python script
From input french_de_grepped.txt, creates output french_de_collated.txt. Used in Step 3 as outlined in introduction to HTML/Rmd file.
Plain Text - 17.7 MB - MD5: e4edbf552b4c8d0c5b9aff493319c7c0
Processed corpus-data files
Output of python script that collates relevant lines from Google n-grams corpus. Second file in data pipeline. Output of Step 3 as outlined in introduction of HTML/Rmd file.
Plain Text - 873.8 MB - MD5: 6423563afeeba4ac933536306a7b4066
Processed corpus-data files
Relevant lines extracted from Google n-grams file. First processed file in pipeline. Output of Step 2 as outlined in introduction of HMTL/Rmd file.
Plain Text - 20.2 MB - MD5: d75f2c12d2724c92851034945a7863ca
Processed corpus-data files
Result of applying hand-coding (with criteria described in HTML/Rmd file) to french_de_collated.txt. Third file in data pipeline. Output of Step 4 as outlined in introduction of HTML/Rmd file.
Plain Text - 28.7 MB - MD5: 9d0cda40c9400e85fbe3be73e5860009
Processed corpus-data files
Result of automatically applying close inferences to french_de_handcoded.txt. Fourth file in data pipeline. Output of step 5 as outlined in introduction of HTML/Rmd file.
Plain Text - 28.7 MB - MD5: fa42be340252421dee09069395df0c7f
Processed corpus-data files
Result of applying further automatic inferences to french_de_inferences.txt. Fifth and final file in data pipeline. All analysis done in R script after this occurs without writing to a new data file. Output of Step 6 as outlined in introduction of HTML/Rmd file.
HTML - 1.5 MB - MD5: 3559b4c0a39990c07b5b33ee6e65a7ce
Master file: start here
HTML-format guide to reproducing the study. Includes narrative, R code, and R output and figures.
Plain Text - 66.6 KB - MD5: 2c239ac2376c451214534e597e3e9336
Mater file generator
Rmd-format file that generates the HTML file. Includes narrative and R code. Open this file in RStudio and use knitr() to re-create HTML file.
Dec 10, 2014 - TROLLing
Makarova, Anastasia; Nesset, Tore, 2014, "Replication data for: Russian nu-drop verbs", https://doi.org/10.18710/HSK0LE, DataverseNO, V2
The spreadsheet "Nu-drop database" includes verbs that are characterized by nu-drop, the process whereby certain verbs with the suffix -nu- omit this morpheme in past tense forms. The verb forms culled from the Russian National Corpus are tagged for phonological, morphological an...
Dec 10, 2014 - TROLLing
Makarova, Anastasia; Nesset, Tore, 2014, "Replication data for: V-temporal adverbials in Slavic", https://doi.org/10.18710/IOCDRU, DataverseNO, V2
The database includes 271 Russian examples and their equivalents in Ukrainian, Belarusian, Polish and Czech. The data were culled from the ParaSol parallel corpus (see http://parasol.unibe.ch/).
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