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improved dataset card

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  1. README.md +35 -28
README.md CHANGED
@@ -4,50 +4,51 @@ annotations_creators:
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  language_creators:
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  - found
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  language:
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- - bg
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- - cs
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- - da
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- - de
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- - el
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  - en
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- - es
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- - et
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- - fi
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- - fr
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  - ga
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- - hr
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- - hu
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- - it
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- - lt
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- - lv
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  - mt
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- - nl
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- - pl
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- - pt
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- - ro
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- - sk
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- - sl
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  - sv
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  license:
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  - cc-by-4.0
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  multilinguality:
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  - multilingual
 
 
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  size_categories:
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- - 1K<n<100K
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  source_datasets:
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- - original
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  task_categories:
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- - token-classification
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  - text-classification
 
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  task_ids:
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  - multi-class-classification
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  - multi-label-classification
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- - named-entity-recognition
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  - topic-classification
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- pretty_name: 'LEXTREME: A Multilingual Legal Benchmark for Natural Language Understanding'
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- tags:
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- - named-entity-recognition-and-classification
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- - judgement-prediction
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  ---
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  # Dataset Card for LEXTREME: A Multilingual Legal Benchmark for Natural Language Understanding
@@ -90,6 +91,12 @@ tags:
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  The dataset consists of 11 diverse multilingual legal NLU tasks. 6 tasks have one single configuration and 5 tasks have two or three configurations. This leads to a total of 18 tasks (8 single-label text classification tasks, 5 multi-label text classification tasks and 5 token-classification tasks).
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  ### Supported Tasks and Leaderboards
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  The dataset supports the tasks of text classification and token classification.
 
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  language_creators:
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  - found
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  language:
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+ - bg
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+ - cs
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+ - da
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+ - de
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+ - el
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  - en
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+ - es
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+ - et
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+ - fi
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+ - fr
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  - ga
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+ - hr
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+ - hu
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+ - it
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+ - lt
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+ - lv
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  - mt
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+ - nl
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+ - pl
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+ - pt
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+ - ro
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+ - sk
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+ - sl
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  - sv
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  license:
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  - cc-by-4.0
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  multilinguality:
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  - multilingual
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+ paperswithcode_id: null
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+ pretty_name: "LEXTREME: A Multilingual Legal Benchmark for Natural Language Understanding"
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  size_categories:
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+ - 10K<n<100K
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  source_datasets:
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+ - extended
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  task_categories:
 
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  - text-classification
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+ - token-classification
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  task_ids:
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  - multi-class-classification
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  - multi-label-classification
 
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  - topic-classification
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+ - text-classification-other-judgement-prediction
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+ - named-entity-recognition
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+ - named entity recognition and classification (NERC)
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+
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  ---
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  # Dataset Card for LEXTREME: A Multilingual Legal Benchmark for Natural Language Understanding
 
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  The dataset consists of 11 diverse multilingual legal NLU tasks. 6 tasks have one single configuration and 5 tasks have two or three configurations. This leads to a total of 18 tasks (8 single-label text classification tasks, 5 multi-label text classification tasks and 5 token-classification tasks).
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+ Use the dataset like this:
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+ ```python
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+ from datasets import load_dataset
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+ dataset = load_dataset("joelito/lextreme", "swiss_judgment_prediction")
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+ ```
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+
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  ### Supported Tasks and Leaderboards
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  The dataset supports the tasks of text classification and token classification.