task_categories:token-classification task_ids:named-entity-recognition annotations_creators:crowdsourced language_creators:found multilinguality:monolingual size_categories:10K<n<100K source_datasets:original language:de license:apache-2.0 region:us
GermaNER is a freely available statistical German Named Entity Tagger based on conditional random fields(CRF). The tagger is trained and evaluated on the NoSta-D Named Entity dataset, which was used in the GermEval 2014 for named entity recognition. The tagger comes close to the performance of the best (proprietary) system in the competition with 77% F-measure (this is the latest result; the one reported in the paper is 76%) test set performance on the four standard NER classes (PERson, LOCation, ORGanisation and OTHer).

We describe a range of features and their influence on German NER classification and provide a comparative evaluation and some analysis of the results. The software components, the training data and all data used for feature generation are distributed under permissive licenses, thus this tagger can be used in academic and commercial settings without restrictions or fees. The tagger is available as a command-line tool and as an Apache UIMA component.
@inproceedings{Benikova2015GermaNERFO,
  title={GermaNER: Free Open German Named Entity Recognition Tool},
  author={Darina Benikova and S. Yimam and Prabhakaran Santhanam and Chris Biemann},
  booktitle={GSCL},
  year={2015}
}
---
annotations_creators:
- crowdsourced
language_creators:
- found
language:
- de
license:
- apache-2.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: GermaNER
dataset_info:
  features:
  - name: id
    dtype: string
  - name: tokens
    sequence: string
  - name: ner_tags
    sequence:
      class_label:
        names:
          '0': B-LOC
          '1': B-ORG
          '2': B-OTH
          '3': B-PER
          '4': I-LOC
          '5': I-ORG
          '6': I-OTH
          '7': I-PER
          '8': O
  splits:
  - name: train
    num_bytes: 9059606
    num_examples: 26200
  download_size: 4363657
  dataset_size: 9059606
---

# Dataset Card for GermaNER

## 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

- **Repository:** https://github.com/tudarmstadt-lt/GermaNER
- **Paper:** https://pdfs.semanticscholar.org/b250/3144ed2152830f6c64a9f797ab3c5a34fee5.pdf
- **Point of Contact:** [Darina Benikova](mailto:benikova@aiphes.tu-darmstadt.de)

### Dataset Summary

[More Information Needed]

### Supported Tasks and Leaderboards

[More Information Needed]

### Languages

German

## Dataset Structure

### Data Instances

An example instance looks as follows:

```
{
  'id': '3',
  'ner_tags': [1, 5, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8],
  'tokens': ['Bayern', 'München', 'ist', 'wieder', 'alleiniger', 'Top-', 'Favorit', 'auf', 'den', 'Gewinn', 'der', 'deutschen', 'Fußball-Meisterschaft', '.']
}
```

### Data Fields

Each instance in the dataset has:
- `id`: an id as a string
- `tokens`: sequence of tokens
- `ner_tags`: NER tags for each token (encoded as IOB)

NER tags can be: 'B-LOC' (0), 'B-ORG' (1), 'B-OTH' (2), 'B-PER' (3), 'I-LOC' (4), 'I-ORG' (5), 'I-OTH' (6), 'I-PER' (7), 'O' (8)

### Data Splits

Dataset provides only train part (26200 data instances).

## 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

License of GermaNER:
```
GermaNER is licensed under ASL 2.0 and other lenient licenses, allowing its use for academic and commercial purposes without restrictions. The licenses of its compenents are mixed licensed and are individually listed in Data/Licenses.

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http://www.apache.org/licenses/

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```

### Citation Information

```bibtex
@inproceedings{Benikova2015GermaNERFO,
  title={GermaNER: Free Open German Named Entity Recognition Tool},
  author={Darina Benikova and Seid Muhie Yimam and P. Santhanam and Chris Biemann},
  booktitle={GSCL},
  year={2015}
}
```

### Contributions

Thanks to [@abhishekkrthakur](https://github.com/abhishekkrthakur) for adding this dataset.