Morris0401/SuZhou_Numerals

Dataset Card for Suzhou Numeral Dataset 🌟

This dataset contains annotated images of Suzhou numerals (0-9) extracted from historical archival records of the Hechang Firm in Nagasaki 📜, documenting trade activities between China, Japan, and Southeast Asia from 1880 to 1930. It’s designed to support research in historical document analysis, optical character recognition (OCR) 🔍, and the study of traditional numeral systems 📊.

Dataset Details 🎉

Dataset Description

This dataset comprises 773 annotated instances of Suzhou numerals derived from the Hechang Firm in Nagasaki archive, a collection of accounting ledgers, trade contracts, and commercial correspondence 💼. The dataset includes high-resolution .png images of Suzhou numerals alongside their corresponding labels in CSV files, capturing natural variations in notation style, stroke thickness, and alignment ✍️. It is split into training (541 samples), testing (116 samples), and validation (116 samples) sets with a 7:1.5:1.5 ratio.

• Curated by: [More Information Needed]
• Funded by [optional]: [More Information Needed]
• Shared by [optional]: [More Information Needed]
• Language(s) (NLP): [More Information Needed]
• License: [More Information Needed]

Dataset Sources [optional] 🔗

• Repository: [More Information Needed]
• Paper [optional]: [More Information Needed]
• Demo [optional]: [More Information Needed]

Uses 🚀

Direct Use ✅

This dataset is suitable for:

• Training OCR models to recognize Suzhou numerals 🤖.
• Studying historical variations in numeral notation and document formatting 📚.
• Benchmarking image classification algorithms on real-world handwritten data 🧪.
  [More Information Needed]

Out-of-Scope Use 🚫

The dataset is not intended for:

• General-purpose digit recognition beyond Suzhou numerals.
• Applications requiring modern numeral systems or non-historical contexts.
  [More Information Needed]

Dataset Structure 🗂️

The dataset is organized as follows:
├── train.csv          # Training set metadata (541 samples)
├── test.csv           # Testing set metadata (116 samples)
├── val.csv            # Validation set metadata (116 samples)
├── images/            # Folder containing 773 individual .png images
│   ├── 12.png         # Example image file
│   ├── 13.png
│   └── ...
├── images.zip         # Zipped archive of the images/ folder

• train.csv, test.csv, val.csv:
  • Columns:
    • image_name: Filename of the image (e.g., 12.png).
    • label: Suzhou numeral label as a string (e.g., 22455).
  • These files map images to their annotated labels.
• images/: Contains all .png images of cropped Suzhou numerals.
• images.zip: A compressed archive of the images/ folder.

The splits were created with a 7:1.5:1.5 ratio to ensure a balanced distribution for training, testing, and validation. [More Information Needed]

Dataset Creation ✨

Curation Rationale

This dataset was created to preserve and analyze the use of Suzhou numerals in historical trade records, enabling research into traditional numeral systems and supporting the development of OCR tools for historical document digitization 🛠️.
[More Information Needed]

Source Data

Data Collection and Processing

The dataset originates from the Hechang Firm in Nagasaki archive, spanning 1880–1930. The process involved:

1. Scanning documents into high-resolution PDFs 📑.
2. Manually identifying and annotating Suzhou numerals (0-9) within transaction records, cost lists, and handwritten text ✍️.
3. Cropping annotated sections into individual .png images, each paired with a label 🖼️.
4. Cross-verifying ambiguous cases (e.g., faded or overlapping strokes) by multiple annotators for consistency ✅.
   [More Information Needed]

Who are the source data producers?

The source data was produced by Chinese merchants and traders associated with the Hechang Firm in Nagasaki, who used Suzhou numerals in their accounting and correspondence 💰. No specific demographic details are available.
[More Information Needed]

Annotations [optional]

Annotation process

Human experts manually annotated Suzhou numerals in the digitized documents. The process included:

• Identifying numeral instances in PDFs 🔍.
• Assigning labels based on the depicted numeral ✍️.
• Cropping images and validating annotations, with multiple annotators resolving ambiguities ✅.
  [More Information Needed]

Who are the annotators?

The annotators were human experts familiar with historical Chinese numerals and document analysis 🧑‍🏫.
[More Information Needed]

Personal and Sensitive Information

The dataset contains no personal or sensitive information, as it focuses solely on numeral images extracted from historical trade records. No identifiable data (e.g., names, addresses) is included 🚫.
[More Information Needed]

Bias, Risks, and Limitations ⚠️

• Bias: The dataset reflects Suzhou numeral usage specific to the Hechang Firm’s records (1880–1930), which may not generalize to other regions or time periods 🌍.
• Risks: Misinterpretation of faded or ambiguous numerals could affect model performance 😕.
• Limitations: Limited sample size (773 instances) and focus on a niche numeral system may restrict broader applicability 📉.
  [More Information Needed]

Recommendations 💡

Users should be aware of the historical and regional specificity of the dataset. For robust OCR applications, supplementing with additional Suzhou numeral data from other sources is recommended 🌟.
Users should be made aware of the risks, biases, and limitations of the dataset. More information needed for further recommendations.

Citation [optional] 📖

BibTeX:

@inproceedings{wu-etal-2025-bringing,
    title = "Bringing Suzhou Numerals into the Digital Age: A Dataset and Recognition Study on {A}ncient {C}hinese Trade Records",
    author = "Wu, Ting-Lin  and
      Chen, Zih-Ching  and
      Chen, Chen-Yuan  and
      Chen, Pi-Jhong  and
      Wang, Li-Chiao",
    editor = "Anderson, Adam  and
      Gordin, Shai  and
      Li, Bin  and
      Liu, Yudong  and
      Passarotti, Marco C.  and
      Sprugnoli, Rachele",
    booktitle = "Proceedings of the Second Workshop on Ancient Language Processing",
    month = may,
    year = "2025",
    address = "The Albuquerque Convention Center, Laguna",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.alp-1.13/",
    pages = "105--111",
    ISBN = "979-8-89176-235-0",
    abstract = "Suzhou numerals, a specialized numerical no-tation system historically used in Chinese com-merce and accounting, played a pivotal role in financial transactions from the Song Dynasty to the early 20th century. Despite their his-torical significance, they remain largely absent from modern OCR benchmarks, limiting com-putational access to archival trade documents. This paper presents a curated dataset of 773 expert-annotated Suzhou numeral samples ex-tracted from late Qing-era trade ledgers. We provide a statistical analysis of character distri-butions, offering insights into their real-world usage in historical bookkeeping. Additionally, we evaluate baseline performance with hand-written text recognition (HTR) model, high-lighting the challenges of recognizing low-resource brush-written numerals. By introduc-ing this dataset and initial benchmark results, we aim to facilitate research in historical doc-umentation in ancient Chinese characters, ad-vancing the digitization of early Chinese finan-cial records. The dataset is publicly available at our huggingface hub, and our codebase can be accessed at our github repository."
}

APA: [More Information Needed]. (2025). Suzhou Numeral Dataset. Hugging Face. [More Information Needed] [More Information Needed]

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