Year: 2018
Type: conference-paper
Abstract: The availability of large scale annotated corpora for coreference is essential to the development of the field.However, creating resources at the required scale via expert annotation would be too expensive.Crowdsourcing has been proposed as an alternative; but this approach has not been widely used for coreference.This paper addresses one crucial hurdle on the way to make this possible, by introducing a new model of annotation for aggregating crowdsourced anaphoric annotations.The model is evaluated along three dimensions: the accuracy of the inferred mention pairs, the quality of the post-hoc constructed silver chains, and the viability of using the silver chains as an alternative to the expert-annotated chains in training a state of the art coreference system.The results suggest that our model can extract from crowdsourced annotations coreference chains of comparable quality to those obtained with expert annotation.
DOI: 10.18653/v1/d18-1218
Institutions: Queen Mary University of London, University of Essex
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W2891045077