The Impact of Grammar Enhancement on Semantic Resources Induction

In this paper describes the effects of the evolution of an Italian dependency grammar on a task of multilingual FrameNet acquisition. The task is based on the creation of virtual English/Italian parallel annotation corpora, which are then aligned at dependency level by using two manually encoded grammar based dependency parsers. We show how the evolution of the LAS (Labeled Attachment Score) metric for the considered grammar has a direct impact on the quality of the induced FrameNet, thus proving that the evolution of the quality of syntactic resources is mirrored by an analogous evolution in semantic ones. In particular we show that an improvement of 30% in LAS causes an improvement of precision for the induced resource ranging from 5% to 10%, depending on the type of evaluation.

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