metadata
language:
- fr
multilinguality:
- monolingual
task_categories:
- token-classification
m1_qualitative_analysis_ref_cmbert_io
Introduction
This dataset was used to perform qualitative analysis of Jean-Baptiste/camembert-ner on nested NER task using Independant NER layers approach [M1]. It contains Paris trade directories entries from the 19th century.
Dataset parameters
- Approach : M1
- Dataset type : ground-truth
- Tokenizer : Jean-Baptiste/camembert-ner
- Tagging format : IO
- Counts :
- Train : 6084
- Dev : 676
- Test : 1685
- Associated fine-tuned models :
- Level-1 : nlpso/m1_ind_layers_ref_cmbert_io_level_1
- Level 2 : nlpso/m1_ind_layers_ref_cmbert_io_level_2
Entity types
| Abbreviation | Entity group (level) | Description |
|---|---|---|
| O | 1 & 2 | Outside of a named entity |
| PER | 1 | Person or company name |
| ACT | 1 & 2 | Person or company professional activity |
| TITREH | 2 | Military or civil distinction |
| DESC | 1 | Entry full description |
| TITREP | 2 | Professionnal reward |
| SPAT | 1 | Address |
| LOC | 2 | Street name |
| CARDINAL | 2 | Street number |
| FT | 2 | Geographical feature |
How to use this dataset
from datasets import load_dataset
train_dev_test = load_dataset("nlpso/m1_qualitative_analysis_ref_cmbert_io")