TROLLing

Getting started with TROLLing Clarino

AcqVA Aurora

Featured Dataverses

In order to use this feature you must have at least one published or linked dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

1,221 to 1,230 of 4,858 Results

Replication Data for: From machine learning to classroom learning: mobile vowels and the Russian preposition v ‘in(to)’ Sep 26, 2023 Nesset, Tore; Xavier, Kevin, 2023, "Replication Data for: From machine learning to classroom learning: mobile vowels and the Russian preposition v ‘in(to)’", https://doi.org/10.18710/ZCDX1B, DataverseNO, V1 The present study reports on a machine learning experiment concerning mobile vowels in the Russian preposition v ‘in(to)’. Data are extracted from the Russian National Corpus. It is shown that a neural network is able to predict mobile vowels in 97.4% of the cases in our dataset, and a decision tree is used to extract a set of three rules that a la...
dataset.csv Sep 26, 2023 - Replication Data for: From machine learning to classroom learning: mobile vowels and the Russian preposition v ‘in(to)’ Comma Separated Values - 4.5 MB - MD5: d467ff9bc56d8ff852f7245e603c106b Database of mobile vowels (Russian preposition v/vo)
dataset_readme.txt Sep 26, 2023 - Replication Data for: From machine learning to classroom learning: mobile vowels and the Russian preposition v ‘in(to)’ Plain Text - 5.1 KB - MD5: 74687b1733fd22176837f3773c06566d Information about the database
Sources and Targets in Kuteva et al. 2019 Sep 15, 2023 Janda, Laura Alexis, 2023, "Sources and Targets in Kuteva et al. 2019", https://doi.org/10.18710/FYFNFV, DataverseNO, V1 This dataset is based on examples found in Kuteva et al. 2019: Kuteva, Tania, Bernd Heine, Bo Hong, Haiping Long, Heiko Narrog, and Seongha Rhee. 2019. World Lexicon of Gramaticalization (2nd ed.). Cambridge: Cambridge University Press. Kuteva et al.’s World Lexicon of Grammaticalization (2019) is an inventory of examples of morphological reanalysi...
00_README.txt Sep 15, 2023 - Sources and Targets in Kuteva et al. 2019 Plain Text - 3.8 KB - MD5: 338f651f83f32d245ce2b6b38fa65900 This is the README file.
01_Data.txt Sep 15, 2023 - Sources and Targets in Kuteva et al. 2019 Plain Text - 5.3 KB - MD5: 357a37f43a0a5f74c4754481fcff1f38 This is the data.
Replication Data for: The long and the short of it: Russian predicate adjectives with zero copula Sep 1, 2023 Janda, Laura Alexis, 2023, "Replication Data for: The long and the short of it: Russian predicate adjectives with zero copula", https://doi.org/10.18710/XKDBLF, DataverseNO, V1 Description of Dataset This is a study of examples of Russian predicate adjectives in clauses with zero-copula present tense, where the adjective is a short form (SF) or a long form nominative (LF). The data was collected in 2022 from SynTagRus (https://universaldependencies.org/treebanks/ru_syntagrus/index.html), the syntactic subcorpus of the Rus...
01README.txt Sep 1, 2023 - Replication Data for: The long and the short of it: Russian predicate adjectives with zero copula Plain Text - 7.0 KB - MD5: 0ea581e1460a4efb6bff66a2112c283a README file
02Dataset.csv Sep 1, 2023 - Replication Data for: The long and the short of it: Russian predicate adjectives with zero copula Comma Separated Values - 2.0 MB - MD5: 14b461380d62fbc2c0ea65316fce4c4b This is the dataset for the analysis in plain text format.
02Dataset.xlsx Sep 1, 2023 - Replication Data for: The long and the short of it: Russian predicate adjectives with zero copula MS Excel Spreadsheet - 1.0 MB - MD5: 296e104817d1ce3c91a0da89cc6234b0 This is the dataset for the analysis in original Excel format.

Replication Data for: From machine learning to classroom learning: mobile vowels and the Russian preposition v ‘in(to)’

Sep 26, 2023

Nesset, Tore; Xavier, Kevin, 2023, "Replication Data for: From machine learning to classroom learning: mobile vowels and the Russian preposition v ‘in(to)’", https://doi.org/10.18710/ZCDX1B, DataverseNO, V1

The present study reports on a machine learning experiment concerning mobile vowels in the Russian preposition v ‘in(to)’. Data are extracted from the Russian National Corpus. It is shown that a neural network is able to predict mobile vowels in 97.4% of the cases in our dataset, and a decision tree is used to extract a set of three rules that a la...

dataset.csv

Sep 26, 2023 - Replication Data for: From machine learning to classroom learning: mobile vowels and the Russian preposition v ‘in(to)’

Comma Separated Values - 4.5 MB -

Database of mobile vowels (Russian preposition v/vo)

dataset_readme.txt

Sep 26, 2023 - Replication Data for: From machine learning to classroom learning: mobile vowels and the Russian preposition v ‘in(to)’

Plain Text - 5.1 KB -

Information about the database

Sources and Targets in Kuteva et al. 2019

Sep 15, 2023

Janda, Laura Alexis, 2023, "Sources and Targets in Kuteva et al. 2019", https://doi.org/10.18710/FYFNFV, DataverseNO, V1

This dataset is based on examples found in Kuteva et al. 2019: Kuteva, Tania, Bernd Heine, Bo Hong, Haiping Long, Heiko Narrog, and Seongha Rhee. 2019. World Lexicon of Gramaticalization (2nd ed.). Cambridge: Cambridge University Press. Kuteva et al.’s World Lexicon of Grammaticalization (2019) is an inventory of examples of morphological reanalysi...

00_README.txt

Sep 15, 2023 - Sources and Targets in Kuteva et al. 2019

Plain Text - 3.8 KB -

This is the README file.

01_Data.txt

Sep 15, 2023 - Sources and Targets in Kuteva et al. 2019

Plain Text - 5.3 KB -

This is the data.

Replication Data for: The long and the short of it: Russian predicate adjectives with zero copula

Sep 1, 2023

Janda, Laura Alexis, 2023, "Replication Data for: The long and the short of it: Russian predicate adjectives with zero copula", https://doi.org/10.18710/XKDBLF, DataverseNO, V1

Description of Dataset This is a study of examples of Russian predicate adjectives in clauses with zero-copula present tense, where the adjective is a short form (SF) or a long form nominative (LF). The data was collected in 2022 from SynTagRus (https://universaldependencies.org/treebanks/ru_syntagrus/index.html), the syntactic subcorpus of the Rus...

01README.txt

Sep 1, 2023 - Replication Data for: The long and the short of it: Russian predicate adjectives with zero copula

Plain Text - 7.0 KB -

README file

02Dataset.csv

Sep 1, 2023 - Replication Data for: The long and the short of it: Russian predicate adjectives with zero copula

Comma Separated Values - 2.0 MB -

This is the dataset for the analysis in plain text format.

02Dataset.xlsx

Sep 1, 2023 - Replication Data for: The long and the short of it: Russian predicate adjectives with zero copula

MS Excel Spreadsheet - 1.0 MB -

This is the dataset for the analysis in original Excel format.

Add Data

Share Dataverse

Link Dataverse

Reset Modifications