多語詞網間對應關係的建立，是多語知識處理的基本要件之一。本文主張多語詞網間的對應關係應該建立在語意關係上，而不是在翻譯或知識本體上。我們將雙語間的對譯關係重新定義為兩個語言間的詞彙語意關係。我們可藉著這些關係的邏輯推論來預測來源語的語意關係是否可在目標語中適用。以上的主張，我們用中文中的210 最常用詞形進行實驗，主要用它們在英語詞網中對譯詞的語意關係作假設的跨語言語意關係轉換。結果顯示跨語言的詞彙語意關係，在符合邏輯推導關係的條件下，可以準確預測。此研究對將來藉助現有語言詞網，為語言資源較貧乏的語言建立新詞網的研究，有正面的意涵。

　　　　　Establishing correspondences between wordnets of different languages is essential to multilingual knowledge processing. We claim that such correspondences must be based on lexical semantic relations, rather than top ontology or word translations. In particular, we define a translation equivalence relation as a bilingual lexical semantic relation. Such relations can then be part of the logical entailment predicting whether source language semantic relations will hold in target language or not. Our claim is tested with a study on 210 Chinese lexical lemmas and their possible semantic-relation links bootstrapped from the Princeton WordNet. The results show that lexical semantic-relation translations are indeed highly precise when they are logically inferable. The study has positive implications for bootstrapping of language wordnets with insufficient monolingual lexical resources.