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In this paper, we show how our methods developed for identifying light verb constructions can be adapted to different domains and different types of texts. We both experiment with rule-based methods and machine learning approaches. Our results indicate that existing solutions for detecting light verb constructions can be successfully applied to other domains as well and we conclude that even a little amount of annotated target data can notably contribute to performance if a bigger corpus fromfatcat:uxotu5b5mbh6jmf5wo4een7pda