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    <abstract>Coreference resolution is the task of grouping together references to the same discourse entity. Resolving coreference in literary texts could benefit a number of Digital Humanities (DH) tasks, such as analyzing the depiction of characters and/or their relations. Domain-dependent training data has shown to improve coreference resolution for many domains, e.g. the biomedical domain, as its properties differ significantly from news text or dialogue, on which automatic systems are typically trained. Literary texts could also benefit from corpora annotated with coreference. We therefore analyze the specific properties of coreference-related phenomena on a number of texts and give directions for the adaptation of annotation guidelines. As some of the adaptations have profound impact, we also present a new annotation tool for coreference, with a focus on enabling annotation of long texts with many discourse entities.</abstract>
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%0 Conference Proceedings
%T Towards Coreference for Literary Text: Analyzing Domain-Specific Phenomena
%A Roesiger, Ina
%A Schulz, Sarah
%A Reiter, Nils
%Y Alex, Beatrice
%Y Degaetano-Ortlieb, Stefania
%Y Feldman, Anna
%Y Kazantseva, Anna
%Y Reiter, Nils
%Y Szpakowicz, Stan
%S Proceedings of the Second Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature
%D 2018
%8 August
%I Association for Computational Linguistics
%C Santa Fe, New Mexico
%F roesiger-etal-2018-towards
%X Coreference resolution is the task of grouping together references to the same discourse entity. Resolving coreference in literary texts could benefit a number of Digital Humanities (DH) tasks, such as analyzing the depiction of characters and/or their relations. Domain-dependent training data has shown to improve coreference resolution for many domains, e.g. the biomedical domain, as its properties differ significantly from news text or dialogue, on which automatic systems are typically trained. Literary texts could also benefit from corpora annotated with coreference. We therefore analyze the specific properties of coreference-related phenomena on a number of texts and give directions for the adaptation of annotation guidelines. As some of the adaptations have profound impact, we also present a new annotation tool for coreference, with a focus on enabling annotation of long texts with many discourse entities.
%U https://aclanthology.org/W18-4515
%P 129-138

Markdown (Informal)

[Towards Coreference for Literary Text: Analyzing Domain-Specific Phenomena](https://aclanthology.org/W18-4515) (Roesiger et al., LaTeCH 2018)

• Towards Coreference for Literary Text: Analyzing Domain-Specific Phenomena (Roesiger et al., LaTeCH 2018)

ACL

• Ina Roesiger, Sarah Schulz, and Nils Reiter. 2018. Towards Coreference for Literary Text: Analyzing Domain-Specific Phenomena. In Proceedings of the Second Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature, pages 129–138, Santa Fe, New Mexico. Association for Computational Linguistics.