Is Japanese CCGBank empirically correct? A case study of passive and causative constructions
Bekki, Daisuke, Yanaka, Hitomi
–arXiv.org Artificial Intelligence
The Japanese CCGBank serves as training and evaluation data for developing Japanese CCG parsers. However, since it is automatically generated from the Kyoto Corpus, a dependency treebank, its linguistic validity still needs to be sufficiently verified. In this paper, we focus on the analysis of passive/causative constructions in the Japanese CCGBank and show that, together with the compositional semantics of ccg2lambda, a semantic parsing system, it yields empirically wrong predictions for the nested construction of passives and causatives.
arXiv.org Artificial Intelligence
Feb-28-2023
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