Thematic Fit Bits: Annotation Quality and Quantity Interplay for Event Participant Representation. (arXiv:2105.06097v2 [cs.CL] UPDATED)

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 …

annotation arxiv event quality representation