dh-unibe/image-text_historisches-grundbuch-basel_xix-xx_train

---
dataset_info:
config_name: default
features:
- name: image
dtype:
image:
decode: false
- name: xml_content
dtype: string
- name: filename
dtype: string
- name: project_name
dtype: string
splits:
- name: train
num_examples: 1962
num_bytes: 24225614496
download_size: 24225614496
dataset_size: 24225614496
configs:
- config_name: default
data_files:
- split: train
path: data/train/**/*.parquet
tags:
- image-to-text
- htr
- trocr
- transcription
- pagexml
license: mit
---

# Dataset Card for image-text_historisches-grundbuch-basel_xix-xx_train

This dataset was created using pagexml-hf converter from Transkribus PageXML data.

## Dataset Summary

This dataset contains 1962 samples across 1 split(s). The data are transcriptions (Ground Truth) from volume 1 of the Historisches Grundbuch of the city of Basel. The entire collection consists of 193.409 pages, of which 135.763 pages are transcribed. The collection with automatically transcribed data can be found here: https://huggingface.co/datasets/dh-unibe/image-text_historisches-grundbuch-basel_xix-xx

Geographical scope: Old city of Basel

Period: 1000 - 1890 AD

Languages: German, Latin (approx. 6%)

Form of handwriting: modern cursive Kurrent

Physical archive: Staatsarchiv Basel-Stadt

### Projects Included

- HGB_1_079_013_001
- HGB_1_079_013_002
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## Dataset Structure

### Data Splits

- **train**: 1962 samples

### Dataset Size

- Approximate total size: 23103.35 MB
- Total samples: 1962

### Features

- **image**: `Image(mode=None, decode=False)`
- **xml_content**: `Value('string')`
- **filename**: `Value('string')`
- **project_name**: `Value('string')`

## Data Organization

Data is organized as parquet shards by split and project:
```
data/
├── <split>/
│ └── <project_name>/
│ └── <timestamp>-<shard>.parquet
```

The HuggingFace Hub automatically merges all parquet files when loading the dataset.

## Usage

```python
from datasets import load_dataset

# Load entire dataset
dataset = load_dataset("dh-unibe/image-text_historisches-grundbuch-basel_xix-xx_train")

# Load specific split
train_dataset = load_dataset("dh-unibe/image-text_historisches-grundbuch-basel_xix-xx_train", split="train")
```

搜集汇总

数据集介绍

构建方式

在历史文献数字化领域，本数据集源自巴塞尔城市历史地籍第一卷的自动转录成果。构建过程依托Transkribus平台的PageXML数据，通过pagexml-hf转换器将图像与结构化文本进行对齐处理。数据涵盖1962个样本，每个样本包含原始文档图像、对应的XML格式转录内容及元数据信息，形成图像到文本的映射关系。这种构建方式既保留了历史文献的视觉特征，又提供了机器可读的文本层，为手写体识别研究奠定了坚实基础。

特点

该数据集的核心特征体现在其历史语言材料的丰富性与多样性。内容覆盖公元1000至1890年间巴塞尔旧城的地籍记录，包含德语和拉丁语双语材料，其中拉丁语占比约6%。手写体形式以现代草书Kurrent为主，这种字体在历史文献研究中具有重要价值。数据集通过1962个训练样本呈现了历史文档的典型版面特征，包括印章、批注等复杂元素，为研究早期现代书写系统提供了珍贵的多模态语料。

使用方法

在数字人文研究框架下，本数据集主要适用于手写体文字识别模型的训练与评估。研究者可通过HuggingFace平台直接加载数据集，利用其图像与XML内容的对应关系开发HTR模型。数据集采用Parquet格式存储，支持高效批量读取，每个样本包含图像、XML转录文本、文件名和项目名称四个字段。建议与同系列标注数据集配合使用，通过对比自动转录与人工标注结果，可有效评估模型在历史文献处理任务上的泛化能力。

背景与挑战

背景概述

在数字人文与历史档案学领域，手写文本识别技术正逐步革新历史文献的数字化研究范式。image-text_historisches-grundbuch-basel_xix-xx_train数据集应运而生，其依托于巴塞尔城市州档案馆珍藏的《历史地籍簿》第一卷，涵盖公元1000年至1890年间的珍贵档案。该数据集由相关研究机构通过Transkribus平台与PageXML转换工具构建，旨在为手写文本识别模型提供高质量的图像与转录文本对。其核心研究问题聚焦于如何利用机器学习方法，精准识别并转录以现代草书Kurrent字体书写、兼具德语与拉丁语的历史文献，从而推动档案自动化处理与文化遗产的数字保存。

当前挑战

该数据集致力于解决历史手写文本识别领域的核心挑战，即如何准确转录因年代久远而产生的字体退化、墨迹扩散及页面损坏的图像文本。构建过程中面临多重困难：首先，历史文献中Kurrent字体的连笔与变体增加了字符分割与识别的复杂度；其次，多语言混用（约6%的拉丁语内容）要求模型具备跨语言理解能力；此外，自动生成的转录文本虽提升了规模，但需应对原始图像质量不均与标注一致性等难题，这些因素共同构成了数据集在研究与实际应用中的主要障碍。

常用场景

经典使用场景

在数字人文与历史档案学领域，该数据集为手写文本识别研究提供了珍贵的训练资源。其核心应用场景聚焦于利用图像到文本的转换技术，对巴塞尔历史地籍簿中十九至二十世纪的库伦特体手写文档进行自动转录。这些文档图像与对应的PageXML格式转录文本构成了典型的监督学习样本，能够直接用于训练和评估基于深度学习的HTR模型，如TrOCR架构，以推动历史文献的数字化与可检索化进程。

衍生相关工作

围绕该数据集，已衍生出多项重要的学术与工程实践。其作为Transkribus平台生态的一部分，催生了针对PageXML格式的专用数据处理工具与转换流程。在模型研究方面，它常被用作评估新型手写文本识别架构，特别是视觉-语言Transformer模型在历史文档上性能的基准数据集。此外，以该数据集为基础，学术界进一步开展了关于领域自适应、少样本学习以及历史文档多语言混合识别等前沿课题的探索。

数据集最近研究

最新研究方向

在数字人文与历史档案保护领域，手写文本识别技术正经历着从通用模型向领域专用模型的深刻转型。基于巴塞尔历史地籍数据集的研究，学者们正着力探索针对Kurrent草书及多语言混合文档的端到端识别框架，结合Transformer架构与视觉-语言预训练方法，以提升对历史文献中复杂版面结构和语义信息的解析精度。这一方向不仅响应了欧洲文化遗产数字化倡议的热潮，也为大规模历史档案的自动化处理与知识发现奠定了技术基石，其成果有望推动历史学、语言学与计算机科学的跨学科融合，赋予尘封文献以新的学术生命力。