
# Dataset Card for Legal Documents Entity Recognition

## Table of Contents
- [Dataset Description](#dataset-description)
  - [Dataset Summary](#dataset-summary)
  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
  - [Languages](#languages)
- [Dataset Structure](#dataset-structure)
  - [Data Instances](#data-instances)
  - [Data Fields](#data-fields)
  - [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
  - [Curation Rationale](#curation-rationale)
  - [Source Data](#source-data)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** https://github.com/elenanereiss/Legal-Entity-Recognition
- **Repository:** None
- **Paper:** https://link.springer.com/chapter/10.1007/978-3-030-33220-4_20
- **Leaderboard:** [If the dataset supports an active leaderboard, add link here]()
- **Point of Contact:** Georg Rehm (georg.rehm@dfki.de)

### Dataset Summary

<div class="course-tip course-tip-orange bg-gradient-to-br dark:bg-gradient-to-r before:border-orange-500 dark:before:border-orange-800 from-orange-50 dark:from-gray-900 to-white dark:to-gray-950 border border-orange-50 text-orange-700 dark:text-gray-400">
  <p><b>Deprecated:</b> Dataset "german_legal_entity_recognition" is deprecated and will be deleted. Use <a href="https://huggingface.co/datasets/elenanereiss/german-ler">"elenanereiss/german-ler"</a> instead.</p>
</div>

### Supported Tasks and Leaderboards

[More Information Needed]

### Languages

[More Information Needed]

## Dataset Structure

### Data Instances

[More Information Needed]

### Data Fields

[More Information Needed]

### Data Splits

[More Information Needed]
## Dataset Creation

### Curation Rationale

[More Information Needed]

### Source Data

[More Information Needed]

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

[More Information Needed]

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

[More Information Needed]

### Citation Information

[More Information Needed]
### Contributions

Thanks to [@abhishekkrthakur](https://github.com/abhishekkrthakur) for adding this dataset.
task_categories:token-classification task_ids:named-entity-recognition annotations_creators:expert-generated language_creators:found multilinguality:monolingual size_categories:n<1K source_datasets:original language:de license:cc-by-4.0 region:us
{"annotations_creators": ["expert-generated"], "language_creators": ["found"], "language": ["de"], "license": ["cc-by-4.0"], "multilinguality": ["monolingual"], "size_categories": ["n<1K"], "source_datasets": ["original"], "task_categories": ["token-classification"], "task_ids": ["named-entity-recognition"], "paperswithcode_id": "legal-documents-entity-recognition", "pretty_name": "Legal Documents Entity Recognition", "dataset_info": [{"config_name": "bag", "features": [{"name": "id", "dtype": "string"}, {"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "B-AN", "1": "B-EUN", "2": "B-GRT", "3": "B-GS", "4": "B-INN", "5": "B-LD", "6": "B-LDS", "7": "B-LIT", "8": "B-MRK", "9": "B-ORG", "10": "B-PER", "11": "B-RR", "12": "B-RS", "13": "B-ST", "14": "B-STR", "15": "B-UN", "16": "B-VO", "17": "B-VS", "18": "B-VT", "19": "I-AN", "20": "I-EUN", "21": "I-GRT", "22": "I-GS", "23": "I-INN", "24": "I-LD", "25": "I-LDS", "26": "I-LIT", "27": "I-MRK", "28": "I-ORG", "29": "I-PER", "30": "I-RR", "31": "I-RS", "32": "I-ST", "33": "I-STR", "34": "I-UN", "35": "I-VO", "36": "I-VS", "37": "I-VT", "38": "O"}}}}], "splits": [{"name": "train"}], "download_size": 4392913, "dataset_size": 0}, {"config_name": "bfh", "features": [{"name": "id", "dtype": "string"}, {"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "B-AN", "1": "B-EUN", "2": "B-GRT", "3": "B-GS", "4": "B-INN", "5": "B-LD", "6": "B-LDS", "7": "B-LIT", "8": "B-MRK", "9": "B-ORG", "10": "B-PER", "11": "B-RR", "12": "B-RS", "13": "B-ST", "14": "B-STR", "15": "B-UN", "16": "B-VO", "17": "B-VS", "18": "B-VT", "19": "I-AN", "20": "I-EUN", "21": "I-GRT", "22": "I-GS", "23": "I-INN", "24": "I-LD", "25": "I-LDS", "26": "I-LIT", "27": "I-MRK", "28": "I-ORG", "29": "I-PER", "30": "I-RR", "31": "I-RS", "32": "I-ST", "33": "I-STR", "34": "I-UN", "35": "I-VO", "36": "I-VS", "37": "I-VT", "38": "O"}}}}], "splits": [{"name": "train"}], "download_size": 4392913, "dataset_size": 0}, {"config_name": "bgh", "features": [{"name": "id", "dtype": "string"}, {"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "B-AN", "1": "B-EUN", "2": "B-GRT", "3": "B-GS", "4": "B-INN", "5": "B-LD", "6": "B-LDS", "7": "B-LIT", "8": "B-MRK", "9": "B-ORG", "10": "B-PER", "11": "B-RR", "12": "B-RS", "13": "B-ST", "14": "B-STR", "15": "B-UN", "16": "B-VO", "17": "B-VS", "18": "B-VT", "19": "I-AN", "20": "I-EUN", "21": "I-GRT", "22": "I-GS", "23": "I-INN", "24": "I-LD", "25": "I-LDS", "26": "I-LIT", "27": "I-MRK", "28": "I-ORG", "29": "I-PER", "30": "I-RR", "31": "I-RS", "32": "I-ST", "33": "I-STR", "34": "I-UN", "35": "I-VO", "36": "I-VS", "37": "I-VT", "38": "O"}}}}], "splits": [{"name": "train"}], "download_size": 4392913, "dataset_size": 0}, {"config_name": "bpatg", "features": [{"name": "id", "dtype": "string"}, {"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "B-AN", "1": "B-EUN", "2": "B-GRT", "3": "B-GS", "4": "B-INN", "5": "B-LD", "6": "B-LDS", "7": "B-LIT", "8": "B-MRK", "9": "B-ORG", "10": "B-PER", "11": "B-RR", "12": "B-RS", "13": "B-ST", "14": "B-STR", "15": "B-UN", "16": "B-VO", "17": "B-VS", "18": "B-VT", "19": "I-AN", "20": "I-EUN", "21": "I-GRT", "22": "I-GS", "23": "I-INN", "24": "I-LD", "25": "I-LDS", "26": "I-LIT", "27": "I-MRK", "28": "I-ORG", "29": "I-PER", "30": "I-RR", "31": "I-RS", "32": "I-ST", "33": "I-STR", "34": "I-UN", "35": "I-VO", "36": "I-VS", "37": "I-VT", "38": "O"}}}}], "splits": [{"name": "train"}], "download_size": 4392913, "dataset_size": 0}, {"config_name": "bsg", "features": [{"name": "id", "dtype": "string"}, {"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "B-AN", "1": "B-EUN", "2": "B-GRT", "3": "B-GS", "4": "B-INN", "5": "B-LD", "6": "B-LDS", "7": "B-LIT", "8": "B-MRK", "9": "B-ORG", "10": "B-PER", "11": "B-RR", "12": "B-RS", "13": "B-ST", "14": "B-STR", "15": "B-UN", "16": "B-VO", "17": "B-VS", "18": "B-VT", "19": "I-AN", "20": "I-EUN", "21": "I-GRT", "22": "I-GS", "23": "I-INN", "24": "I-LD", "25": "I-LDS", "26": "I-LIT", "27": "I-MRK", "28": "I-ORG", "29": "I-PER", "30": "I-RR", "31": "I-RS", "32": "I-ST", "33": "I-STR", "34": "I-UN", "35": "I-VO", "36": "I-VS", "37": "I-VT", "38": "O"}}}}], "splits": [{"name": "train"}], "download_size": 4392913, "dataset_size": 0}, {"config_name": "bverfg", "features": [{"name": "id", "dtype": "string"}, {"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "B-AN", "1": "B-EUN", "2": "B-GRT", "3": "B-GS", "4": "B-INN", "5": "B-LD", "6": "B-LDS", "7": "B-LIT", "8": "B-MRK", "9": "B-ORG", "10": "B-PER", "11": "B-RR", "12": "B-RS", "13": "B-ST", "14": "B-STR", "15": "B-UN", "16": "B-VO", "17": "B-VS", "18": "B-VT", "19": "I-AN", "20": "I-EUN", "21": "I-GRT", "22": "I-GS", "23": "I-INN", "24": "I-LD", "25": "I-LDS", "26": "I-LIT", "27": "I-MRK", "28": "I-ORG", "29": "I-PER", "30": "I-RR", "31": "I-RS", "32": "I-ST", "33": "I-STR", "34": "I-UN", "35": "I-VO", "36": "I-VS", "37": "I-VT", "38": "O"}}}}], "splits": [{"name": "train"}], "download_size": 4392913, "dataset_size": 0}, {"config_name": "bverwg", "features": [{"name": "id", "dtype": "string"}, {"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "B-AN", "1": "B-EUN", "2": "B-GRT", "3": "B-GS", "4": "B-INN", "5": "B-LD", "6": "B-LDS", "7": "B-LIT", "8": "B-MRK", "9": "B-ORG", "10": "B-PER", "11": "B-RR", "12": "B-RS", "13": "B-ST", "14": "B-STR", "15": "B-UN", "16": "B-VO", "17": "B-VS", "18": "B-VT", "19": "I-AN", "20": "I-EUN", "21": "I-GRT", "22": "I-GS", "23": "I-INN", "24": "I-LD", "25": "I-LDS", "26": "I-LIT", "27": "I-MRK", "28": "I-ORG", "29": "I-PER", "30": "I-RR", "31": "I-RS", "32": "I-ST", "33": "I-STR", "34": "I-UN", "35": "I-VO", "36": "I-VS", "37": "I-VT", "38": "O"}}}}], "splits": [{"name": "train"}], "download_size": 4392913, "dataset_size": 0}, {"config_name": "all", "features": [{"name": "id", "dtype": "string"}, {"name": "tokens", "sequence": "string"}, {"name": "ner_tags", "sequence": {"class_label": {"names": {"0": "B-AN", "1": "B-EUN", "2": "B-GRT", "3": "B-GS", "4": "B-INN", "5": "B-LD", "6": "B-LDS", "7": "B-LIT", "8": "B-MRK", "9": "B-ORG", "10": "B-PER", "11": "B-RR", "12": "B-RS", "13": "B-ST", "14": "B-STR", "15": "B-UN", "16": "B-VO", "17": "B-VS", "18": "B-VT", "19": "I-AN", "20": "I-EUN", "21": "I-GRT", "22": "I-GS", "23": "I-INN", "24": "I-LD", "25": "I-LDS", "26": "I-LIT", "27": "I-MRK", "28": "I-ORG", "29": "I-PER", "30": "I-RR", "31": "I-RS", "32": "I-ST", "33": "I-STR", "34": "I-UN", "35": "I-VO", "36": "I-VS", "37": "I-VT", "38": "O"}}}}], "splits": [{"name": "train"}], "download_size": 4392913, "dataset_size": 0}]}
TAGS
#task_categories-token-classification #task_ids-named-entity-recognition #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-n<1K #source_datasets-original #language-German #license-cc-by-4.0 #region-us 


# Dataset Card for Legal Documents Entity Recognition

## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions

## Dataset Description

- Homepage: URL
- Repository: None
- Paper: URL
- Leaderboard: [If the dataset supports an active leaderboard, add link here]()
- Point of Contact: Georg Rehm (URL@URL)

### Dataset Summary

<div class="course-tip course-tip-orange bg-gradient-to-br dark:bg-gradient-to-r before:border-orange-500 dark:before:border-orange-800 from-orange-50 dark:from-gray-900 to-white dark:to-gray-950 border border-orange-50 text-orange-700 dark:text-gray-400">
  <p><b>Deprecated:</b> Dataset "german_legal_entity_recognition" is deprecated and will be deleted. Use <a href="URL instead.</p>
</div>

### Supported Tasks and Leaderboards



### Languages



## Dataset Structure

### Data Instances



### Data Fields



### Data Splits


## Dataset Creation

### Curation Rationale



### Source Data



#### Initial Data Collection and Normalization



#### Who are the source language producers?



### Annotations



#### Annotation process



#### Who are the annotators?



### Personal and Sensitive Information



## Considerations for Using the Data

### Social Impact of Dataset



### Discussion of Biases



### Other Known Limitations



## Additional Information

### Dataset Curators



### Licensing Information






### Contributions

Thanks to @abhishekkrthakur for adding this dataset.
# Dataset Card for Legal Documents Entity Recognition ## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions ## Dataset Description

- Homepage: URL
- Repository: None
- Paper: URL
- Leaderboard: [If the dataset supports an active leaderboard, add link here]()
- Point of Contact: Georg Rehm (URL@URL) ### Dataset Summary

<div class="course-tip course-tip-orange bg-gradient-to-br dark:bg-gradient-to-r before:border-orange-500 dark:before:border-orange-800 from-orange-50 dark:from-gray-900 to-white dark:to-gray-950 border border-orange-50 text-orange-700 dark:text-gray-400">
  <p><b>Deprecated:</b> Dataset "german_legal_entity_recognition" is deprecated and will be deleted. Use <a href="URL instead.</p>
</div> ### Supported Tasks and Leaderboards ### Languages ## Dataset Structure ### Data Instances ### Data Fields ### Data Splits ## Dataset Creation ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators ### Licensing Information ### Contributions

Thanks to @abhishekkrthakur for adding this dataset.
TAGS
#task_categories-token-classification #task_ids-named-entity-recognition #annotations_creators-expert-generated #language_creators-found #multilinguality-monolingual #size_categories-n<1K #source_datasets-original #language-German #license-cc-by-4.0 #region-us 
 # Dataset Card for Legal Documents Entity Recognition ## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions ## Dataset Description

- Homepage: URL
- Repository: None
- Paper: URL
- Leaderboard: [If the dataset supports an active leaderboard, add link here]()
- Point of Contact: Georg Rehm (URL@URL) ### Dataset Summary

<div class="course-tip course-tip-orange bg-gradient-to-br dark:bg-gradient-to-r before:border-orange-500 dark:before:border-orange-800 from-orange-50 dark:from-gray-900 to-white dark:to-gray-950 border border-orange-50 text-orange-700 dark:text-gray-400">
  <p><b>Deprecated:</b> Dataset "german_legal_entity_recognition" is deprecated and will be deleted. Use <a href="URL instead.</p>
</div> ### Supported Tasks and Leaderboards ### Languages ## Dataset Structure ### Data Instances ### Data Fields ### Data Splits ## Dataset Creation ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators ### Licensing Information ### Contributions

Thanks to @abhishekkrthakur for adding this dataset.