Replication Data for: Correspondence Analysis of the Natural and Specialized Perfectives of the Russian verb putat’
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset contains the database and statistical code used for a term paper in HIF-3082 Quantitative Methods in Linguistics, spring 2017. It includes two datasets (I and II). Dataset I is used for a synchronic analysis of the verb cluster putat’ ‘mix up, mess up, confuse, tangle’ in Russian. There are seven verbs in the analysis: the simplex imperfective putat’ and six of its perfectives. Dataset I involves 1400 examples from the Russian National Corpus (years 1950-2016) that are tagged with semantic category of the verbs’ patients. Based on these semantic categories, I run a Correspondence Analysis to explore the relationship between verb and type of patient. Dataset II involves 295 examples from the Russian National Corpus (years 1800-1849) of the same verbs. The examples are tagged with the same semantic categories of patients as th' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Correspondence Analysis","Natural Perfectives","Russian aspect","Specialized Perfectives","Synchrony vs. diachrony"]} <|eot_id|>
 Here is the Description of a dataset. Description:'This dataset contains the database and statistical code used for a term paper in HIF-3082 Quantitative Methods in Linguistics, spring 2017. It includes two datasets (I and II). Dataset I is used for a synchronic analysis of the verb cluster putat’ ‘mix up, mess up, confuse, tangle’ in Russian. There are seven verbs in the analysis: the simplex imperfective putat’ and six of its perfectives. Dataset I involves 1400 examples from the Russian National Corpus (years 1950-2016) that are tagged with semantic category of the verbs’ patients. Based on these semantic categories, I run a Correspondence Analysis to explore the relationship between verb and type of patient. Dataset II involves 295 examples from the Russian National Corpus (years 1800-1849) of the same verbs. The examples are tagged with the same semantic categories of patients as th' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
This dataset contains the database and statistical code used for a term paper in HIF-3082 Quantitative Methods in Linguistics, spring 2017. It includes two datasets (I and II). Dataset I is used for a synchronic analysis of the verb cluster putat’ ‘mix up, mess up, confuse, tangle’ in Russian. There are seven verbs in the analysis: the simplex imperfective putat’ and six of its perfectives. Dataset I involves 1400 examples from the Russian National Corpus (years 1950-2016) that are tagged with semantic category of the verbs’ patients. Based on these semantic categories, I run a Correspondence Analysis to explore the relationship between verb and type of patient. Dataset II involves 295 examples from the Russian National Corpus (years 1800-1849) of the same verbs. The examples are tagged with the same semantic categories of patients as th
Correspondence Analysis; Natural Perfectives; Russian aspect; Specialized Perfectives; Synchrony vs. diachrony