Recursive atomic decomposition of CJK characters with 9-grid 2-digit spatial encoding. 将汉字递归拆解为原子部件,并在 9 宫格 2 位数字空间编码中标记每个组件的位置。
Project description
cjk-semantic-split
中文简介
cjk-semantic-split 是一个 Python 库,用于将任意 CJK 统一表意文字递归拆分为原子部件,并使用 9 宫格 2 位数字空间编码标记每个组件的位置。
核心特性
- 递归拆解:例如
踩 → 足 + 采 → 爪 + 木,中间非叶节点(如采)完整保留 - 位置编码:每个组件的 2 位数字代号(
00/10/20/30/40四个基本方位 +50/60/70/80四个角方位 +14/16/34/36四分拆壁 +90–99包围框) - 组合算子
⊙:父子位置按空间几何合成(详见docs/component-position-encoding.md) - 多重数据源:内置四级 — Unihan kIDS / wikimedia Commons / 下一层采集 / 手工修补
- 零运行时依赖:纯 Python
主要 API
decompose(text)→ 字符串(默认 JSON 输出)read_structure(text)→list[DecompositionTree],保留完整嵌套层级(包含中间非叶节点)python -m chinese_decompose <字符>→ 命令行
from chinese_decompose import read_structure
trees = read_structure("踩")
# trees[0].atoms == ('足', '爪', '木')
# trees[0].positions == (30, 60, 80)
# 采 作为中间节点保留在 children[1] 中
详细算法参见 docs/decomposition-logic.md;完整位置编码表参见 docs/component-position-encoding.md。
Recursive atomic decomposition of CJK characters with 9-grid spatial position encoding.
pip install cjk-semantic-split
from chinese_decompose import decompose
decompose("踩")
# '踩 [30]:足 [60]:爪 [80]:木'
decompose("囚")
# '囚 [90]:囗 [0]:人'
decompose("踩好", as_tree=True)
# [DecompositionTree('踩'), DecompositionTree('好')]
# Read the full structural decomposition (preserves intermediate nodes
# like 采 inside 踩; each tree node carries its 2-digit position code).
from chinese_decompose import read_structure
trees = read_structure("踩")
trees[0].atoms # ('足', '爪', '木')
trees[0].positions # (30, 60, 80)
trees[0].children[1].char # '采' (intermediate node preserved!)
trees[0].children[1].position # 40
Documentation
- Component Position Encoding — full position-code reference (00/10/20/30/40, corners, 4-cell strips, surrounds) and the composition operator.
- Decomposition Logic — algorithm walkthrough, data flow, worked example
踩 → 足 + 采 → 爪 + 木.
Position Encoding
Every component sits at a 2-digit position code: cardinals (10/20/30/40), single-cell corners (50/60/70/80), 4-cell layout strips (14/16/34/36), or surround envelopes (90–99). See the design spec for full details.
CLI
python -m chinese_decompose 踩 # JSON output (default)
python -m chinese_decompose 踩 --format dsl # DSL string
python -m chinese_decompose 踩 --format tree # repr() of nested trees
python -m chinese_decompose --self-test # coverage report
Data Sources
Decomposition data is bundled for offline use. Coverage extends across four tiers:
- Tier 1 (Unihan kIDS): ~21k chars
- Tier 2 (wikimedia Commons): ~22k chars
- Tier 3 (next-layer harvest): ~80k chars
- Tier 4 (manual patches): dispute-case overrides
Last-wins resolution: patches > l3 > l2 > l1.
Configuration
from chinese_decompose import set_primitives
set_primitives({"木", "火", "水", ...}) # process-local override
License
MIT — see LICENSE.
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