|
|
--- |
|
|
license: mit |
|
|
task_categories: |
|
|
- token-classification |
|
|
language: |
|
|
- en |
|
|
tags: |
|
|
- legal |
|
|
pretty_name: TAB |
|
|
size_categories: |
|
|
- 1K<n<10K |
|
|
--- |
|
|
|
|
|
# Dataset Card for the Text Anonymization Benchmark (TAB) |
|
|
|
|
|
## Dataset Description |
|
|
|
|
|
- **Repository:** |
|
|
- **Paper:** [The Text Anonymization Benchmark (TAB): A Dedicated Corpus and Evaluation Framework for Text Anonymization](https://aclanthology.org/2022.cl-4.19/) |
|
|
- **Point of Contact:** [Pierre Lison](mailto:plison@nr.no), [Ildikó Pilán](mailto:pilan@nr.no) |
|
|
|
|
|
## Dataset Summary |
|
|
|
|
|
This repository contains the v1.0 release of the Text Anonymization Benchmark, a corpus for text anonymization. |
|
|
The corpus comprises 1,268 English-language court cases from the [European Court for Human Rights (ECHR)](https://www.echr.coe.int/). The documents were manually annotated with information about personal identifiers (including their semantic category and need for masking), confidential attributes and co-reference relations. |
|
|
Some documents were annotated by multiple annotators. |
|
|
|
|
|
## Data format |
|
|
The data is distributed in a standoff JSON format consisting of a list of document object with the following information: |
|
|
|
|
|
| Variable name | Description | |
|
|
|---------------|-------------| |
|
|
| entity_mentions | a list of entity mention objects with annotations (see table below) | |
|
|
| dataset_type | which data split the court case belongs to (train /dev / test) | |
|
|
| doc_id | the ID of the court case (e.g. “001-61807”) | |
|
|
| annotator_id | the ID of the annotator | |
|
|
| meta | an object with metadata for each case (year, countries and legal articles involved etc.) | |
|
|
| quality_checked | whether the document was revised by another annotator | |
|
|
| task | the target of the anonymisation task (i.g. who to anonymise) | |
|
|
| text | the text of the court case used during the annotation | |
|
|
|
|
|
Each entity mention object under 'entity_mentions' has the following attributes: |
|
|
|
|
|
| Variable name | Description | |
|
|
|---------------|-------------| |
|
|
| entity_type | the semantic category of the entity (e.g. PERSON) | |
|
|
| entity_mention_id | ID of the entity mention | |
|
|
| start_offset | start character offset of the annotated span | |
|
|
| end_offset | end character offset of the annotated span | |
|
|
| span_text | the text of the annotated span | |
|
|
| edit_type | type of annotator action for the mention (check / insert / correct) | |
|
|
| identifier_type | the need for masking, masked if 'DIRECT' or 'QUASI', 'NO_MASK' otherwise | |
|
|
| entity_id | ID of the entity the entity mention is related to in meaning | |
|
|
| confidential_status | category of a potential source of discrimination (e.g. beliefs, sexual orientation etc.) | |
|
|
|
|
|
Note. The structure of this version of TAB is somewhat flatter than the one distributed on the [GitHub TAB repository](https://github.com/NorskRegnesentral/text-anonymization-benchmark). |
|
|
|
|
|
## License |
|
|
|
|
|
TAB is released under an MIT License. |
|
|
|
|
|
The MIT License is a short and simple permissive license allowing both commercial and non-commercial use of the software. The only requirement is to preserve the copyright and license notices (see file [License](https://github.com/NorskRegnesentral/text-anonymisation-benchmark/blob/master/LICENSE.txt)). Licensed works, modifications, and larger works may be distributed under different terms and without source code. |
