Datasets:
Update README.md
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README.md
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num_examples: 182
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download_size: 5673825
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dataset_size: 13943099
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- config_name:
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features:
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- name: ID-LICITACAO
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dtype: float64
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path: bidCorpus_synthetic/test-*
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- split: validation
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path: bidCorpus_synthetic/validation-*
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- config_name:
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data_files:
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- split: train
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path:
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tags:
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- legal
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---
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<tr><td>bidCorpus_qual_weak_sup</td><td><a href="">-</a></td><td>Seção de Habilitação de Editais de Licitação</td><td>Multi-label Classification</td><td>7</td></tr>
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<tr><td>bidCorpus_synthetic</td><td><a href="">-</a></td><td>Seção de Habilitação de Editais de Licitação</td><td>Multi-label Classification</td><td>7</td></tr>
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<tr><td>bidCorpus_sections_type</td><td><a href="">-</a></td><td>Seções de Editais de Licitação</td><td>Multi-label Classification</td><td>5</td></tr>
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<tr><td>
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</table>
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#### bidCorpus_NER_keyphrase
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The dataset provides a systematic approach to categorize the various sections found in bidding notices, facilitating better organization and analysis of procurement documents.
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####
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This dataset consists of raw, unlabeled texts from sections of bidding notices. The sections included are:
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}
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```
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####
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An example of 'train' looks as follows.
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```json
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- `text`: a list of `string` features (list of factual paragraphs from the case description).
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- `label`: a list of `string` features (classification labels for sections types).
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####
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- `ID-LICITACAO`: a list of `float64` features (auction ID).
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- `ID-ARQUIVO`: a list of `float64` features (file ID).
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<td>1.530</td>
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</tr>
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<tr>
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<td>
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<td>373.650</td>
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<td>N/A</td>
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<td>N/A</td>
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num_examples: 182
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download_size: 5673825
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dataset_size: 13943099
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- config_name: bidCorpus_raw
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features:
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- name: ID-LICITACAO
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dtype: float64
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path: bidCorpus_synthetic/test-*
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- split: validation
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path: bidCorpus_synthetic/validation-*
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- config_name: bidCorpus_raw
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data_files:
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- split: train
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path: bidCorpus_raw/train-*
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tags:
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- legal
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---
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<tr><td>bidCorpus_qual_weak_sup</td><td><a href="">-</a></td><td>Seção de Habilitação de Editais de Licitação</td><td>Multi-label Classification</td><td>7</td></tr>
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<tr><td>bidCorpus_synthetic</td><td><a href="">-</a></td><td>Seção de Habilitação de Editais de Licitação</td><td>Multi-label Classification</td><td>7</td></tr>
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<tr><td>bidCorpus_sections_type</td><td><a href="">-</a></td><td>Seções de Editais de Licitação</td><td>Multi-label Classification</td><td>5</td></tr>
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<tr><td>bidCorpus_raw</td><td><a href="">-</a></td><td>Seções de Editais de Licitação</td><td>n/a</td><td>n/a</td></tr>
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</table>
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#### bidCorpus_NER_keyphrase
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The dataset provides a systematic approach to categorize the various sections found in bidding notices, facilitating better organization and analysis of procurement documents.
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#### bidCorpus_raw
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This dataset consists of raw, unlabeled texts from sections of bidding notices. The sections included are:
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}
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```
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#### bidCorpus_raw
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An example of 'train' looks as follows.
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```json
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- `text`: a list of `string` features (list of factual paragraphs from the case description).
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- `label`: a list of `string` features (classification labels for sections types).
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#### bidCorpus_raw
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- `ID-LICITACAO`: a list of `float64` features (auction ID).
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- `ID-ARQUIVO`: a list of `float64` features (file ID).
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<td>1.530</td>
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</tr>
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<tr>
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<td>bidCorpus_raw</td>
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<td>373.650</td>
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<td>N/A</td>
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<td>N/A</td>
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