Automatically constructing Wordnet synsets
This addresses the problem of reducing expert time and effort in building Wordnets for both resource-rich and resource-poor languages, though it appears incremental as it builds on existing resources.
The paper tackles the challenge of manually constructing Wordnets by proposing algorithms to automatically generate Wordnet synsets for various languages, using existing Wordnets, machine translation, and bilingual dictionaries, achieving results applicable to any language with an English-to-target bilingual dictionary.
Manually constructing a Wordnet is a difficult task, needing years of experts' time. As a first step to automatically construct full Wordnets, we propose approaches to generate Wordnet synsets for languages both resource-rich and resource-poor, using publicly available Wordnets, a machine translator and/or a single bilingual dictionary. Our algorithms translate synsets of existing Wordnets to a target language T, then apply a ranking method on the translation candidates to find best translations in T. Our approaches are applicable to any language which has at least one existing bilingual dictionary translating from English to it.