Datasets:
Tasks:
Token Classification
Modalities:
Text
Formats:
json
Sub-tasks:
named-entity-recognition
Size:
10K - 100K
License:
| annotations_creators: | |
| - other | |
| language_creators: | |
| - found | |
| language: | |
| - multilingual | |
| - bg | |
| - cs | |
| - da | |
| - de | |
| - el | |
| - en | |
| - es | |
| - et | |
| - fi | |
| - fr | |
| - ga | |
| - hu | |
| - it | |
| - lt | |
| - lv | |
| - mt | |
| - nl | |
| - pt | |
| - ro | |
| - sk | |
| - sv | |
| license: | |
| - cc-by-4.0 | |
| multilinguality: | |
| - multilingual | |
| size_categories: | |
| - 1K<n<10K | |
| source_datasets: | |
| - original | |
| task_categories: | |
| - token-classification | |
| task_ids: | |
| - named-entity-recognition | |
| pretty_name: Spanish Datasets for Sensitive Entity Detection in the Legal Domain | |
| tags: | |
| - named-entity-recognition-and-classification | |
| # Dataset Card for Multilingual European Datasets for Sensitive Entity Detection in the Legal Domain | |
| ## Table of Contents | |
| - [Table of Contents](#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:** | |
| - ** | |
| Repository:** [Spanish](https://elrc-share.eu/repository/browse/mapa-anonymization-package-spanish/b550e1a88a8311ec9c1a00155d026706687917f92f64482587c6382175dffd76/), [Most](https://elrc-share.eu/repository/search/?q=mfsp:3222a6048a8811ec9c1a00155d0267067eb521077db54d6684fb14ce8491a391), [German, Portuguese, Slovak, Slovenian, Swedish](https://elrc-share.eu/repository/search/?q=mfsp:833df1248a8811ec9c1a00155d0267067685dcdb77064822b51cc16ab7b81a36) | |
| - **Paper:** de Gibert Bonet, O., García Pablos, A., Cuadros, M., & Melero, M. (2022). Spanish Datasets for Sensitive | |
| Entity Detection in the Legal Domain. Proceedings of the Language Resources and Evaluation Conference, June, | |
| 3751–3760. http://www.lrec-conf.org/proceedings/lrec2022/pdf/2022.lrec-1.400.pdf | |
| - **Leaderboard:** | |
| - **Point of Contact:** [Joel Niklaus](mailto:[email protected]) | |
| ### Dataset Summary | |
| The dataset consists of 12 documents (9 for Spanish due to parsing errors) taken from EUR-Lex, a multilingual corpus of court | |
| decisions and legal dispositions in the 24 official languages of the European Union. The documents have been annotated | |
| for named entities following the guidelines of the [MAPA project]( https://mapa-project.eu/) which foresees two | |
| annotation level, a general and a more fine-grained one. The annotated corpus can be used for named entity recognition/classification. | |
| ### Supported Tasks and Leaderboards | |
| The dataset supports the task of Named Entity Recognition and Classification (NERC). | |
| ### Languages | |
| The following languages are supported: bg, cs, da, de, el, en, es, et, fi, fr, ga, hu, it, lt, lv, mt, nl, pt, ro, sk, sv | |
| ## Dataset Structure | |
| ### Data Instances | |
| The file format is jsonl and three data splits are present (train, validation and test). Named Entity annotations are | |
| non-overlapping. | |
| ### Data Fields | |
| For the annotation the documents have been split into sentences. The annotations has been done on the token level. | |
| The files contain the following data fields | |
| - `language`: language of the sentence | |
| - `type`: The document type of the sentence. Currently, only EUR-LEX is supported. | |
| - `file_name`: The document file name the sentence belongs to. | |
| - `sentence_number`: The number of the sentence inside its document. | |
| - `tokens`: The list of tokens in the sentence. | |
| - `coarse_grained`: The coarse-grained annotations for each token | |
| - `fine_grained`: The fine-grained annotations for each token | |
| As previously stated, the annotation has been conducted on a global and a more fine-grained level. | |
| The tagset used for the global and the fine-grained named entities is the following: | |
| - Address | |
| - Building | |
| - City | |
| - Country | |
| - Place | |
| - Postcode | |
| - Street | |
| - Territory | |
| - Amount | |
| - Unit | |
| - Value | |
| - Date | |
| - Year | |
| - Standard Abbreviation | |
| - Month | |
| - Day of the Week | |
| - Day | |
| - Calender Event | |
| - Person | |
| - Age | |
| - Ethnic Category | |
| - Family Name | |
| - Financial | |
| - Given Name – Female | |
| - Given Name – Male | |
| - Health Insurance Number | |
| - ID Document Number | |
| - Initial Name | |
| - Marital Status | |
| - Medical Record Number | |
| - Nationality | |
| - Profession | |
| - Role | |
| - Social Security Number | |
| - Title | |
| - Url | |
| - Organisation | |
| - Time | |
| - Vehicle | |
| - Build Year | |
| - Colour | |
| - License Plate Number | |
| - Model | |
| - Type | |
| The final coarse grained tagset (in IOB notation) is the following: | |
| `['O', 'B-ORGANISATION', 'I-ORGANISATION', 'B-ADDRESS', 'I-ADDRESS', 'B-DATE', 'I-DATE', 'B-PERSON', 'I-PERSON', 'B-AMOUNT', 'I-AMOUNT', 'B-TIME', 'I-TIME']` | |
| The final fine grained tagset (in IOB notation) is the following: | |
| `[ | |
| 'O', | |
| 'B-BUILDING', | |
| 'I-BUILDING', | |
| 'B-CITY', | |
| 'I-CITY', | |
| 'B-COUNTRY', | |
| 'I-COUNTRY', | |
| 'B-PLACE', | |
| 'I-PLACE', | |
| 'B-TERRITORY', | |
| 'I-TERRITORY', | |
| 'I-UNIT', | |
| 'B-UNIT', | |
| 'B-VALUE', | |
| 'I-VALUE', | |
| 'B-YEAR', | |
| 'I-YEAR', | |
| 'B-STANDARD ABBREVIATION', | |
| 'I-STANDARD ABBREVIATION', | |
| 'B-MONTH', | |
| 'I-MONTH', | |
| 'B-DAY', | |
| 'I-DAY', | |
| 'B-AGE', | |
| 'I-AGE', | |
| 'B-ETHNIC CATEGORY', | |
| 'I-ETHNIC CATEGORY', | |
| 'B-FAMILY NAME', | |
| 'I-FAMILY NAME', | |
| 'B-INITIAL NAME', | |
| 'I-INITIAL NAME', | |
| 'B-MARITAL STATUS', | |
| 'I-MARITAL STATUS', | |
| 'B-PROFESSION', | |
| 'I-PROFESSION', | |
| 'B-ROLE', | |
| 'I-ROLE', | |
| 'B-NATIONALITY', | |
| 'I-NATIONALITY', | |
| 'B-TITLE', | |
| 'I-TITLE', | |
| 'B-URL', | |
| 'I-URL', | |
| 'B-TYPE', | |
| 'I-TYPE', | |
| ]` | |
| ### Data Splits | |
| Splits created by Joel Niklaus. | |
| | language | # train files | # validation files | # test files | # train sentences | # validation sentences | # test sentences | | |
| |:-----------|----------------:|---------------------:|---------------:|--------------------:|-------------------------:|-------------------:| | |
| | bg | 9 | 1 | 2 | 1411 | 166 | 560 | | |
| | cs | 9 | 1 | 2 | 1464 | 176 | 563 | | |
| | da | 9 | 1 | 2 | 1455 | 164 | 550 | | |
| | de | 9 | 1 | 2 | 1457 | 166 | 558 | | |
| | el | 9 | 1 | 2 | 1529 | 174 | 584 | | |
| | en | 9 | 1 | 2 | 893 | 98 | 408 | | |
| | es | 7 | 1 | 1 | 806 | 248 | 155 | | |
| | et | 9 | 1 | 2 | 1391 | 163 | 516 | | |
| | fi | 9 | 1 | 2 | 1398 | 187 | 531 | | |
| | fr | 9 | 1 | 2 | 1297 | 97 | 490 | | |
| | ga | 9 | 1 | 2 | 1383 | 165 | 515 | | |
| | hu | 9 | 1 | 2 | 1390 | 171 | 525 | | |
| | it | 9 | 1 | 2 | 1411 | 162 | 550 | | |
| | lt | 9 | 1 | 2 | 1413 | 173 | 548 | | |
| | lv | 9 | 1 | 2 | 1383 | 167 | 553 | | |
| | mt | 9 | 1 | 2 | 937 | 93 | 442 | | |
| | nl | 9 | 1 | 2 | 1391 | 164 | 530 | | |
| | pt | 9 | 1 | 2 | 1086 | 105 | 390 | | |
| | ro | 9 | 1 | 2 | 1480 | 175 | 557 | | |
| | sk | 9 | 1 | 2 | 1395 | 165 | 526 | | |
| | sv | 9 | 1 | 2 | 1453 | 175 | 539 | | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| *„[…] to our knowledge, there exist no open resources annotated for NERC [Named Entity Recognition and Classificatio] in Spanish in the legal domain. With the | |
| present contribution, we intend to fill this gap. With the release of the created resources for fine-tuning and | |
| evaluation of sensitive entities detection in the legal domain, we expect to encourage the development of domain-adapted | |
| anonymisation tools for Spanish in this field“* (de Gibert Bonet et al., 2022) | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| The dataset consists of documents taken from EUR-Lex corpus which is publicly available. No further | |
| information on the data collection process are given in de Gibert Bonet et al. (2022). | |
| #### Who are the source language producers? | |
| The source language producers are presumably lawyers. | |
| ### Annotations | |
| #### Annotation process | |
| *"The annotation scheme consists of a complex two level hierarchy adapted to the legal domain, it follows the scheme | |
| described in (Gianola et al., 2020) […] Level 1 entities refer to general categories (PERSON, DATE, TIME, ADDRESS...) | |
| and level 2 entities refer to more fine-grained subcategories (given name, personal name, day, year, month...). Eur-Lex, | |
| CPP and DE have been annotated following this annotation scheme […] The manual annotation was performed using | |
| INCePTION (Klie et al., 2018) by a sole annotator following the guidelines provided by the MAPA consortium."* (de Gibert | |
| Bonet et al., 2022) | |
| #### Who are the annotators? | |
| Only one annotator conducted the annotation. More information are not provdided in de Gibert Bonet et al. (2022). | |
| ### 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 | |
| Note that the dataset at hand presents only a small portion of a bigger corpus as described in de Gibert Bonet et al. | |
| (2022). At the time of writing only the annotated documents from the EUR-Lex corpus were available. | |
| Note that the information given in this dataset card refer to the dataset version as provided by Joel Niklaus and Veton | |
| Matoshi. The dataset at hand is intended to be part of a bigger benchmark dataset. Creating a benchmark dataset | |
| consisting of several other datasets from different sources requires postprocessing. Therefore, the structure of the | |
| dataset at hand, including the folder structure, may differ considerably from the original dataset. In addition to that, | |
| differences with regard to dataset statistics as give in the respective papers can be expected. The reader is advised to | |
| have a look at the conversion script ```convert_to_hf_dataset.py``` in order to retrace the steps for converting the | |
| original dataset into the present jsonl-format. For further information on the original dataset structure, we refer to | |
| the bibliographical references and the original Github repositories and/or web pages provided in this dataset card. | |
| ## Additional Information | |
| ### Dataset Curators | |
| The names of the original dataset curators and creators can be found in references given below, in the section *Citation | |
| Information*. Additional changes were made by Joel Niklaus ([Email](mailto:[email protected]) | |
| ; [Github](https://github.com/joelniklaus)) and Veton Matoshi ([Email](mailto:[email protected]) | |
| ; [Github](https://github.com/kapllan)). | |
| ### Licensing Information | |
| [Attribution 4.0 International (CC BY 4.0) ](https://creativecommons.org/licenses/by/4.0/) | |
| ### Citation Information | |
| ``` | |
| @article{DeGibertBonet2022, | |
| author = {{de Gibert Bonet}, Ona and {Garc{\'{i}}a Pablos}, Aitor and Cuadros, Montse and Melero, Maite}, | |
| journal = {Proceedings of the Language Resources and Evaluation Conference}, | |
| number = {June}, | |
| pages = {3751--3760}, | |
| title = {{Spanish Datasets for Sensitive Entity Detection in the Legal Domain}}, | |
| url = {https://aclanthology.org/2022.lrec-1.400}, | |
| year = {2022} | |
| } | |
| ``` | |
| ### Contributions | |
| Thanks to [@JoelNiklaus](https://github.com/joelniklaus) and [@kapllan](https://github.com/kapllan) for adding this | |
| dataset. | |