民数记 33:21

Chinese Union Version with Strong's Numbers (Traditional)

ℹ️

关于此译本

Chinese Union Version with Strong's Numbers (Traditional)

形式对等来源: Chinese Union Version (Traditional)最佳用途: in-depth word studies

🎯 翻译方法

A study-focused edition of the Chinese Union Version in Traditional characters enhanced with Strong's numbering to link Chinese terms to their underlying Hebrew and Greek words. Retains the formal style of the CUV while adding lexical reference markers.

直译程度

4/5

可读性

3/5

💎 特色

Strong's numbering integration: Each verse includes Strong's reference numbers to the underlying Hebrew and Greek terms for precise lexical study.
Traditional Chinese script: Text presented in Traditional characters for regions and readers that prefer 繁體中文.
Study-oriented layout: Numbering and reference markers support analysis over smooth reading flow.
MySword import source: Edition sourced from MySword distribution for compatibility with study tools.
Formal CUV base text: Retains the established diction and structure of the Chinese Union Version.

✅ 优点

Direct linkage to original Hebrew/Greek via Strong's numbers
Widely recognized CUV text in Traditional script
Useful for word studies and lexical analysis
Consistent verse structure for cross-referencing

⚠️ 注意事项

Archaic/formal phrasing may challenge modern readers
Strong's numbering can interrupt reading flow
Best suited for readers comfortable with Traditional Chinese characters
Not optimized for devotional or casual reading

👥 适用人群

适合

Chinese readers who prefer Traditional characters
pastors and teachers
students of biblical languages
serious Bible study and exegesis users
word-study enthusiasts

不太适合

children and new readers
casual or devotional reading
readers who prefer Simplified Chinese
those seeking contemporary language style

🔄 对比

Chinese Union Version (Revised)Chinese Union Version (Simplified)Chinese Contemporary Bible (CCB)Today's Chinese Version (TCV)

附加资源

引用经文

申 1:1 : 1 ¶ 以下所記的是摩西在約但河東的曠野、疏弗對面的亞拉巴 ─就是巴蘭、陀弗、拉班、哈洗錄、底撒哈中間─向以色列眾人所說的話。

相似经文（AI）

这些经文通过 AI 驱动的语义相似度（基于含义与上下文）找到。结果偶尔可能包含意想不到的关联。