Datasets:
Tasks:
Token Classification
Sub-tasks:
named-entity-recognition
Languages:
Portuguese
Size:
n<1K
License:
| annotations_creators: | |
| - expert-generated | |
| language_creators: | |
| - found | |
| language: | |
| - pt | |
| license: | |
| - unknown | |
| multilinguality: | |
| - monolingual | |
| size_categories: | |
| - n<1K | |
| source_datasets: | |
| - original | |
| task_categories: | |
| - token-classification | |
| task_ids: | |
| - named-entity-recognition | |
| paperswithcode_id: null | |
| pretty_name: HAREM | |
| dataset_info: | |
| - config_name: default | |
| features: | |
| - name: id | |
| dtype: string | |
| - name: tokens | |
| sequence: string | |
| - name: ner_tags | |
| sequence: | |
| class_label: | |
| names: | |
| 0: O | |
| 1: B-PESSOA | |
| 2: I-PESSOA | |
| 3: B-ORGANIZACAO | |
| 4: I-ORGANIZACAO | |
| 5: B-LOCAL | |
| 6: I-LOCAL | |
| 7: B-TEMPO | |
| 8: I-TEMPO | |
| 9: B-VALOR | |
| 10: I-VALOR | |
| 11: B-ABSTRACCAO | |
| 12: I-ABSTRACCAO | |
| 13: B-ACONTECIMENTO | |
| 14: I-ACONTECIMENTO | |
| 15: B-COISA | |
| 16: I-COISA | |
| 17: B-OBRA | |
| 18: I-OBRA | |
| 19: B-OUTRO | |
| 20: I-OUTRO | |
| splits: | |
| - name: test | |
| num_bytes: 1062714 | |
| num_examples: 128 | |
| - name: train | |
| num_bytes: 1506373 | |
| num_examples: 121 | |
| - name: validation | |
| num_bytes: 51318 | |
| num_examples: 8 | |
| download_size: 1887281 | |
| dataset_size: 2620405 | |
| - config_name: selective | |
| features: | |
| - name: id | |
| dtype: string | |
| - name: tokens | |
| sequence: string | |
| - name: ner_tags | |
| sequence: | |
| class_label: | |
| names: | |
| 0: O | |
| 1: B-PESSOA | |
| 2: I-PESSOA | |
| 3: B-ORGANIZACAO | |
| 4: I-ORGANIZACAO | |
| 5: B-LOCAL | |
| 6: I-LOCAL | |
| 7: B-TEMPO | |
| 8: I-TEMPO | |
| 9: B-VALOR | |
| 10: I-VALOR | |
| splits: | |
| - name: test | |
| num_bytes: 1062714 | |
| num_examples: 128 | |
| - name: train | |
| num_bytes: 1506373 | |
| num_examples: 121 | |
| - name: validation | |
| num_bytes: 51318 | |
| num_examples: 8 | |
| download_size: 1715873 | |
| dataset_size: 2620405 | |
| # Dataset Card for HAREM | |
| ## 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:** [HAREM homepage](https://www.linguateca.pt/primeiroHAREM/harem_coleccaodourada_en.html) | |
| - **Repository:** [HAREM repository](https://www.linguateca.pt/primeiroHAREM/harem_coleccaodourada_en.html) | |
| - **Paper:** [HAREM: An Advanced NER Evaluation Contest for Portuguese](http://comum.rcaap.pt/bitstream/10400.26/76/1/SantosSecoCardosoVilelaLREC2006.pdf) | |
| - **Point of Contact:** [Diana Santos](mailto:[email protected]) | |
| ### Dataset Summary | |
| The HAREM is a Portuguese language corpus commonly used for Named Entity Recognition tasks. It includes about 93k words, from 129 different texts, | |
| from several genres, and language varieties. The split of this dataset version follows the division made by [1], where 7% HAREM | |
| documents are the validation set and the miniHAREM corpus (with about 65k words) is the test set. There are two versions of the dataset set, | |
| a version that has a total of 10 different named entity classes (Person, Organization, Location, Value, Date, Title, Thing, Event, | |
| Abstraction, and Other) and a "selective" version with only 5 classes (Person, Organization, Location, Value, and Date). | |
| It's important to note that the original version of the HAREM dataset has 2 levels of NER details, namely "Category" and "Sub-type". | |
| The dataset version processed here ONLY USE the "Category" level of the original dataset. | |
| [1] Souza, Fábio, Rodrigo Nogueira, and Roberto Lotufo. "BERTimbau: Pretrained BERT Models for Brazilian Portuguese." Brazilian Conference on Intelligent Systems. Springer, Cham, 2020. | |
| ### Supported Tasks and Leaderboards | |
| [More Information Needed] | |
| ### Languages | |
| Portuguese | |
| ## Dataset Structure | |
| ### Data Instances | |
| ``` | |
| { | |
| "id": "HAREM-871-07800", | |
| "ner_tags": [3, 0, 0, 3, 4, 4, 4, 4, 4, 4, 4, 4, | |
| ], | |
| "tokens": [ | |
| "Abraço", "Página", "Principal", "ASSOCIAÇÃO", "DE", "APOIO", "A", "PESSOAS", "COM", "VIH", "/", "SIDA" | |
| ] | |
| } | |
| ``` | |
| ### Data Fields | |
| - `id`: id of the sample | |
| - `tokens`: the tokens of the example text | |
| - `ner_tags`: the NER tags of each token | |
| The NER tags correspond to this list: | |
| ``` | |
| "O", "B-PESSOA", "I-PESSOA", "B-ORGANIZACAO", "I-ORGANIZACAO", "B-LOCAL", "I-LOCAL", "B-TEMPO", "I-TEMPO", "B-VALOR", "I-VALOR", "B-ABSTRACCAO", "I-ABSTRACCAO", "B-ACONTECIMENTO", "I-ACONTECIMENTO", "B-COISA", "I-COISA", "B-OBRA", "I-OBRA", "B-OUTRO", "I-OUTRO" | |
| ``` | |
| The NER tags have the same format as in the CoNLL shared task: a B denotes the first item of a phrase and an I any non-initial word. | |
| ### Data Splits | |
| The data is split into train, validation and test set for each of the two versions (default and selective). The split sizes are as follow: | |
| | Train | Val | Test | | |
| | ------ | ----- | ---- | | |
| | 121 | 8 | 128 | | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| [More Information Needed] | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| [More Information Needed] | |
| #### Who are the source language producers? | |
| [More Information Needed] | |
| ### Annotations | |
| #### 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 | |
| ``` | |
| @inproceedings{santos2006harem, | |
| title={Harem: An advanced ner evaluation contest for portuguese}, | |
| author={Santos, Diana and Seco, Nuno and Cardoso, Nuno and Vilela, Rui}, | |
| booktitle={quot; In Nicoletta Calzolari; Khalid Choukri; Aldo Gangemi; Bente Maegaard; Joseph Mariani; Jan Odjik; Daniel Tapias (ed) Proceedings of the 5 th International Conference on Language Resources and Evaluation (LREC'2006)(Genoa Italy 22-28 May 2006)}, | |
| year={2006} | |
| } | |
| ``` | |
| ### Contributions | |
| Thanks to [@jonatasgrosman](https://github.com/jonatasgrosman) for adding this dataset. |