Ran0/JieZi

{
  "image": "images/U+4E00/K/1.png",
  "question": "请识别图中的字形，并阐述其文字学属性。",
  "answer": "该字在现代字典中字头作「一」，图示为楷书字形。就造字法与结构而言，该字属独体结构之指事字...",
  "character": "一",
  "script": "楷书",
  "task": "analysis"
}

{
  "character": "一",
  "script": "楷书",
  "creation_method": ["指事字"],
  "structure": "独体",
  "special_structure": "独体",
  "components": [
    {"component": "一", "function": ["表意"], "explanation": "象一根算筹横置之形"}
  ],
  "original_meaning": "数目一",
  "evolution": "甲骨文、金文、战国文字、篆书皆象一根算筹横置之形...",
  "pinyin": ["yī"],
  "meaning_chunks": [
    {"pinyin": "yī", "pos": "数词", "meaning": "数目一", "notes": "本义", "examples": ""}
  ],
  "images": ["JieZi-Dataset/images/U+4E00/K/1.png", "JieZi-Dataset/images/U+4E00/K/2.png"]
}

from datasets import load_dataset

# Load from the Hub
dataset = load_dataset("Ran0/JieZi", split="train")

# Inspect a sample
sample = dataset[0]
print(sample["question"])   # 请识别图中的字形，并阐述其文字学属性。
print(sample["answer"])     # 该字在现代字典中字头作「㐁」...
print(sample["character"])  # 㐁 (modern standard character)
print(sample["script"])     # 楷书 (script type)
print(sample["task"])       # analysis (task type)
sample["image"].show()      # Display the character image

import json
from pathlib import Path

root = Path("JieZi-Dataset")
with (root / "JieZi-Dataset.jsonl").open("r", encoding="utf-8") as f:
    for line in f:
        item = json.loads(line)
        image_path = root / item["image"]   # relative path
        question   = item["question"]
        answer     = item["answer"]
        character  = item["character"]
        script     = item["script"]
        task       = item["task"]
        # ... your processing logic ...

import json

# Load metadata for a specific character-script pair
with open("metadata/楷书/一_楷书.json", "r", encoding="utf-8") as f:
    meta = json.load(f)

print(meta["character"])       # 一
print(meta["creation_method"]) # ['指事字']
print(meta["structure"])       # 独体
print(meta["components"])      # [{'component': '一', 'function': ['表意'], 'explanation': '...'}]
print(meta["pinyin"])          # ['yī']
print(meta["meaning_chunks"])  # list of meaning entries with POS, examples, etc.
print(meta["images"])          # ['JieZi-Dataset/images/U+4E00/K/1.png', ...]

JieZi/
├── JieZi-Dataset/
│   ├── JieZi-Dataset.jsonl    # Main dataset file (505,867 VQA records, shuffled)
│   └── images/                # Glyph image directory (132,544 images)
│       ├── U+4E00/            # Unicode folder for character "一"
│       │   ├── J/             # 甲骨文 (Jiaguwen / Oracle Bone)
│       │   ├── K/             # 楷书 (Kaishu / Regular — MegaHan97K)
│       │   └── ...
│       ├── U+4E01/            # Unicode folder for character "丁"
│       │   ├── B/             # 金文 (Jinwen / Bronze)
│       │   ├── S/             # 篆书 (Zhuanshu / Seal)
│       │   └── ...
│       └── ...                # One folder per character (U+XXXX)
├── metadata/                  # Character metadata (36,131 JSON files)
│   ├── 隶书/                  #   8,662 files
│   ├── 篆书/                  #   8,679 files
│   ├── 草书/                  #   8,580 files
│   ├── 楷书/                  #   6,923 files (includes chars without VQA images)
│   ├── 金文/                  #   1,655 files
│   ├── 甲骨文/                #   1,226 files
│   └── 战国文字/              #     406 files
├── JieZi-bench/               # Benchmark subset (512 hard characters)
│   ├── hard_04EB5_亵/         # One folder per benchmark character
│   │   ├── entry.json         # Character metadata & annotations
│   │   └── images/            # Glyph images for this character
│   └── ...
├── README.md                  # Dataset documentation (this file)
└── main_figure.png            # Project teaser figure

@misc{jiezi2024,
  title={JieZi: A Large-Scale Expert-Audited Dataset and Benchmark for Ancient Chinese Character Exegesis},
  author={Ran et al.},
  year={2024},
  howpublished={\url{https://huggingface.co/datasets/Ran0/JieZi}}
}