Web: http://arxiv.org/abs/2105.06097

May 5, 2022, 1:11 a.m. | Yuval Marton, Asad Sayeed

cs.CL updates on arXiv.org arxiv.org

Modeling thematic fit (a verb--argument compositional semantics task)
currently requires a very large burden of labeled data. We take a
linguistically machine-annotated large corpus and replace corpus layers with
output from higher-quality, more modern taggers. We compare the old and new
corpus versions' impact on a verb--argument fit modeling task, using a
high-performing neural approach. We discover that higher annotation quality
dramatically reduces our data requirement while demonstrating better supervised
predicate-argument classification. But in applying the model to
psycholinguistic tasks …

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