nlpso/m0_qualitative_analysis_ocr_ptrn_cmbert_io

---
language:
- fr
multilinguality:
- monolingual
task_categories:
- token-classification
---

# m0_qualitative_analysis_ocr_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 : noisy (Pero OCR)
* 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_ocr_ptrn_cmbert_io](https://huggingface.co/nlpso/m0_flat_ner_ocr_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_ocr_ptrn_cmbert_io")

原始信息汇总

数据集概述

数据集名称

m0_qualitative_analysis_ocr_ptrn_cmbert_io

数据集描述

该数据集用于对HueyNemud/das22-10-camembert_pretrained模型进行定性分析，针对扁平NER任务采用M0方法。数据集包含19世纪巴黎贸易目录的条目。

数据集参数

• 方法 : M0
• 数据集类型 : 噪声数据（Pero OCR）
• 分词器 : HueyNemud/das22-10-camembert_pretrained
• 标记格式 : IO
• 数据集大小 :
  • 训练集 : 6084
  • 验证集 : 676
  • 测试集 : 1685
• 关联的微调模型 : nlpso/m0_flat_ner_ocr_ptrn_cmbert_io

实体类型

缩写	描述
O	非实体部分
PER	人名或公司名
ACT	职业活动
TITRE	荣誉称号
LOC	街道名称
CARDINAL	街道号码
FT	地理特征

如何使用此数据集

python from datasets import load_dataset

train_dev_test = load_dataset("nlpso/m0_qualitative_analysis_ocr_ptrn_cmbert_io")