3,471 to 3,480 of 5,139 Results
R Syntax - 2.9 KB -
MD5: 70537a260531e957d68f3532b2587a4b
R script that analyses the data from the fiction register (rus.fiction.tab, original format csv). |
R Syntax - 3.5 KB -
MD5: 50b6fb2ee6e498085b53cb030db06fa5
R script that analyses the data from the scientific-technical register (rus.scitech_corrected.tab, original format csv). |
R Syntax - 5.7 KB -
MD5: 5f50d30c39beb01d7c7fe869b693cab9
R script that takes care of the analysis of verbs by derivational morpology and semantics. Uses the three dataset files fic50_factor1tagged.tab, journ50_factor1tagged.tab and scitech50_factor1tagged.tab (original format csv). |
Tabular Data - 12.4 KB - 8 Variables, 225 Observations - UNF:6:FcLokpcNo9/lqGqnJr8/Fg==
Lemmas from the fiction dataset with a frequency of 50+, tagged for a number of features.
Columns:
lemma (verb lemma),
factor1 (factor 1 coordinate value from the correspondence analysis)
asp (aspect label tag, levels: i(mperfective), p(erfective), b(iaspectual))
freq (frequency)
morph1 (morphological type 1, levels: 1Impv (simplex imperfec... |
Tabular Data - 10.4 KB - 8 Variables, 185 Observations - UNF:6:i5RDeUNEke185uknffIvNQ==
Lemmas from the journalistic dataset with a frequency of 50+, tagged for a number of features.
Columns:
lemma (verb lemma),
factor1 (factor 1 coordinate value from the correspondence analysis)
asp (aspect label tag, levels: i(mperfective), p(erfective), b(iaspectual))
freq (frequency)
morph1 (morphological type 1, levels: 1Impv (simplex imp... |
Tabular Data - 4.6 MB - 1 Variables, 78084 Observations - UNF:6:Qvntfkg9Nzf20k7M+Vi4lA==
Dataset for the fiction register, extracted from the Russian National Corpus. Columns:
FormTranslit (transliterated form)
LemmaTranslit (transliterated lemma)
MoodTense (mood and tense of the verb combined)
Trans (transitivity, levels: intr(ansitive), trans(itive))
Voice (voice of the verb, levels: act(ive), med (middle), pass(ive))
VoicePar... |
Tabular Data - 3.2 MB - 1 Variables, 52716 Observations - UNF:6:rGFY0vp0eA7zN5+s5q19GQ==
Dataset for the journalistic register, extracted from the Russian National Corpus.
Columns:
FormTranslit (transliterated form)
LemmaTranslit (transliterated lemma)
MoodTense (mood and tense of the verb combined)
Trans (transitivity, levels: intr(ansitive), trans(itive))
Voice (voice of the verb, levels: act(ive), med (middle), pass(ive))
V... |
Tabular Data - 2.8 MB - 1 Variables, 43528 Observations - UNF:6:7JWXykZeJAzpCsOhSolXpQ==
Dataset for the scientific-technical register, extracted from the Russian National Corpus. Columns:
FormTranslit (transliterated form)
LemmaTranslit (transliterated lemma)
MoodTense (mood and tense of the verb combined)
Trans (transitivity, levels: intr(ansitive), trans(itive))
Voice (voice of the verb, levels: act(ive), med (middle), pass(iv... |
Tabular Data - 10.3 KB - 8 Variables, 172 Observations - UNF:6:RDO6l2SoPtSoBKdY0RjAEQ==
Lemmas from the scientific-technical dataset with a frequency of 50+, tagged for a number of features.
Columns:
lemma (verb lemma),
factor1 (factor 1 coordinate value from the correspondence analysis)
asp (aspect label tag, levels: i(mperfective), p(erfective), b(iaspectual))
freq (frequency)
morph1 (morphological type 1, levels: 1Impv (sim... |
Aug 9, 2017
Ji, Yinglin; Hohenstein, Jill, 2017, "Replication Data for: English and Chinese children’s motion event similarity judgments", https://doi.org/10.18710/AAZVJH, DataverseNO, V1
This study explores the relationship between language and thought in similarity judgments by testing how monolingual children who speak languages with partial typological differences in motion description (English and Chinese) respond to visual motion stimuli. Participants were, either Chinese- or English-speaking, 3-year-olds, 8-year-olds and adul... |
