We demonstrate the benefits of a multilingual approach to automatic lexical semantic verb classification based on statistical analysis of corpora in multiple languages. Our research incorporates two interrelated threads. In one, we exploit the similarities in the crosslinguis-tic classification of verbs, to extend work on English verb classification to a new language (Italian), and to new classes within that language, achieving an accuracy of 86.4% (baseline 33.9%). Our second strand of research exploits the differences across languages in the syntactic expression of semantic properties, to show that complementary information about English verbs can be extracted from their translations in a second language (Chinese). The use of multilingual features improves classification performance of the English verbs, achieving an accuracy of 83.5% (baseline 33.3%).
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