Year: 2010
Type: conference-paper
Abstract: The task of coreference resolution requires people or systems to decide when two referring expressions refer to the 'same' entity or event.In real text, this is often a difficult decision because identity is never adequately defined, leading to contradictory treatment of cases in previous work.This paper introduces the concept of 'near-identity', a middle ground category between identity and non-identity, to handle such cases systematically.We present a typology of Near-Identity Relations (NIDENT) that includes fifteen types-grouped under four main families-that capture a wide range of ways in which (near-)coreference relations hold between discourse entities.We validate the theoretical model by annotating a small sample of real data and showing that inter-annotator agreement is high enough for stability (K= 0.58, and up to K= 0.65 and K= 0.84 when leaving out one and two outliers, respectively).This work enables subsequent creation of the first internally consistent language resource of this type through larger annotation efforts.
Authors: Marta Recasens, Eduard Hovy, M. Antònia Martí
Institutions: Universitat de Barcelona, University of Southern California
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W1529628505