| language: | |
| - fr | |
| multilinguality: | |
| - monolingual | |
| task_categories: | |
| - token-classification | |
| # m0_qualitative_analysis_ref_ptrn_cmbert_io | |
| ## Introduction | |
| This dataset was used to perform **qualitative analysis** of [HueyNemud/das22-10-camembert_pretrained](https://huggingface.co/HueyNemud/das22-10-camembert_pretrained) on **flat NER task** using Flat NER approach [M0]. | |
| It contains 19th-century Paris trade directories' entries. | |
| ## Dataset parameters | |
| * Approach : M0 | |
| * Dataset type : ground-truth | |
| * Tokenizer : [HueyNemud/das22-10-camembert_pretrained](https://huggingface.co/HueyNemud/das22-10-camembert_pretrained) | |
| * Tagging format : IO | |
| * Counts : | |
| * Train : 6084 | |
| * Dev : 676 | |
| * Test : 1685 | |
| * Associated fine-tuned model : [nlpso/m0_flat_ner_ref_ptrn_cmbert_io](https://huggingface.co/nlpso/m0_flat_ner_ref_ptrn_cmbert_io) | |
| ## Entity types | |
| Abbreviation|Description | |
| -|- | |
| O |Outside of a named entity | |
| PER |Person or company name | |
| ACT |Person or company professional activity | |
| TITRE |Distinction | |
| LOC |Street name | |
| CARDINAL |Street number | |
| FT |Geographical feature | |
| ## How to use this dataset | |
| ```python | |
| from datasets import load_dataset | |
| train_dev_test = load_dataset("nlpso/m0_qualitative_analysis_ref_ptrn_cmbert_io") | |