Unsupervised Word Class Induction for Under-resourced Languages: A Case Study on Indonesian

Abstract

In this study we investigate how we can learn both: (a) syntactic classes that capture the range of predicate argument structures (PASs) of a word and the syntactic alternations it participates in, but ignore large semantic differences in the component words; and (b) syntactico-semantic classes that capture PAS and alternation properties, but are also semantically coherent (a la Levin classes). We focus on Indonesian as our case study, a language that is spoken by more than 165 million speakers, but is nonetheless relatively under-resourced in terms of NLP. In particular, we focus on the syntactic variation that arises with the affixing of the Indonesian suffix -kan, which varies according t..