Supersense and Sensibility: Proxy Tasks for Semantic Annotation of Prepositions
Luke Gessler, Shira Wein, Nathan Schneider

TL;DR
This paper introduces two proxy tasks—surface substitution and similarity judgments—to efficiently annotate prepositional supersenses, aiming to reduce expert effort while maintaining annotation quality.
Contribution
It proposes novel, practical methods for semantic annotation of prepositions that are comparable to expert annotations, facilitating scalable linguistic analysis.
Findings
Both methods show potential for high-quality annotations
Pilot studies indicate comparable quality to expert annotations
Methods are efficient and scalable for semantic annotation
Abstract
Prepositional supersense annotation is time-consuming and requires expert training. Here, we present two sensible methods for obtaining prepositional supersense annotations by eliciting surface substitution and similarity judgments. Four pilot studies suggest that both methods have potential for producing prepositional supersense annotations that are comparable in quality to expert annotations.
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Taxonomy
TopicsTopic Modeling · Natural Language Processing Techniques · Speech and dialogue systems
