bigscience-workshop / bigscience-workshop/data_tooling

Create dataset vicon_visim400

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Description

- uid: vicon_visim400
- type: processed
- description:
- name: Vietnamese Datasets for Evaluating Semantic Models of (Dis-)Similarity and Relatedness (ViCon and ViSim-400)
- description: This dataset consists of two kinds of datasets: The first dataset, namely ViCon, comprises pairs of synonyms and antonymys across noun, verb, and adjective classes, offerring data to distinguish between similarity and dissimilarity. The second dataset ViSim-400 is a dataset of semantic relation pairs which contains degrees of similarity across five semantic relations, as rated by human judges.
- homepage: https://www.ims.uni-stuttgart.de/forschung/ressourcen/experiment-daten/vnese-sem-datasets/
- validated: True
- languages:
- language_names:
- Vietnamese
- language_comments:
- language_locations:
- Western Europe
- Germany
- validated: False
- custodian:
- name: Thang Vu
- in_catalogue:
- type: A university or research institution
- location: Germany
- contact_name: Thang Vu
- contact_email: ngoc-thang.vu@ims.uni-stuttgart.de
- contact_submitter: False
- additional:
- validated: False
- availability:
- procurement:
- for_download: Yes - it has a direct download link or links
- download_url: https://www.ims.uni-stuttgart.de/documents/ressourcen/experiment-daten/ViData.zip
- download_email:
- licensing:
- has_licenses: Unclear
- license_text:
- license_properties:
- license_list:
- pii:
- has_pii: No
- generic_pii_likely:
- generic_pii_list:
- numeric_pii_likely:
- numeric_pii_list:
- sensitive_pii_likely:
- sensitive_pii_list:
- no_pii_justification_class: general knowledge not written by or referring to private persons
- no_pii_justification_text:
- validated: False
- processed_from_primary:
- from_primary: Original data
- primary_availability:
- primary_license:
- primary_types:
- validated: False
- media:
- category:
- text
- text_format:
- audiovisual_format:
- image_format:
- database_format:
- .ZIP
- text_is_transcribed: No
- instance_type: article
- instance_count: 100

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