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Here we describe work on learning the subcategories of verbs in amorphologically rich language using only minimal linguistic resources. Our goalis to learn verb subcategorizations for Quechua, an under-resourcedmorphologically rich language, from an unannotated corpus. We compare resultsfrom applying this approach to an unannotated Arabic corpus with those achievedby processing the same text in treebank form. The original plan was to use onlya morphological analyzer and an unannotated corpus, but experiments suggestthat this approach by itself will not be effective for learning thecombinatorial potential of Arabic verbs in general. The lower bound onresources for acquiring this information is somewhat higher, apparentlyrequiring a a part-of-speech tagger and chunker for most languages, and amorphological disambiguater for Arabic.

Considering a resource-light approach to learning verb valencies