@inproceedings{de-langhe-etal-2023-leveraging,
title = "Leveraging Structural Discourse Information for Event Coreference Resolution in {D}utch",
author = "De Langhe, Loic and
De Clercq, Orphee and
Hoste, Veronique",
editor = "Strube, Michael and
Braud, Chloe and
Hardmeier, Christian and
Li, Junyi Jessy and
Loaiciga, Sharid and
Zeldes, Amir",
booktitle = "Proceedings of the 4th Workshop on Computational Approaches to Discourse (CODI 2023)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.codi-1.5",
doi = "10.18653/v1/2023.codi-1.5",
pages = "48--53",
abstract = "We directly embed easily extractable discourse structure information (subsection, paragraph and text type) in a transformer-based Dutch event coreference resolution model in order to more explicitly provide it with structural information that is known to be important in coreferential relationships. Results show that integrating this type of knowledge leads to a significant improvement in CONLL F1 for within-document settings (+ 8.6{\textbackslash}{\%}) and a minor improvement for cross-document settings (+ 1.1{\textbackslash}{\%}).",
}
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<abstract>We directly embed easily extractable discourse structure information (subsection, paragraph and text type) in a transformer-based Dutch event coreference resolution model in order to more explicitly provide it with structural information that is known to be important in coreferential relationships. Results show that integrating this type of knowledge leads to a significant improvement in CONLL F1 for within-document settings (+ 8.6\textbackslash%) and a minor improvement for cross-document settings (+ 1.1\textbackslash%).</abstract>
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%0 Conference Proceedings
%T Leveraging Structural Discourse Information for Event Coreference Resolution in Dutch
%A De Langhe, Loic
%A De Clercq, Orphee
%A Hoste, Veronique
%Y Strube, Michael
%Y Braud, Chloe
%Y Hardmeier, Christian
%Y Li, Junyi Jessy
%Y Loaiciga, Sharid
%Y Zeldes, Amir
%S Proceedings of the 4th Workshop on Computational Approaches to Discourse (CODI 2023)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F de-langhe-etal-2023-leveraging
%X We directly embed easily extractable discourse structure information (subsection, paragraph and text type) in a transformer-based Dutch event coreference resolution model in order to more explicitly provide it with structural information that is known to be important in coreferential relationships. Results show that integrating this type of knowledge leads to a significant improvement in CONLL F1 for within-document settings (+ 8.6\textbackslash%) and a minor improvement for cross-document settings (+ 1.1\textbackslash%).
%R 10.18653/v1/2023.codi-1.5
%U https://aclanthology.org/2023.codi-1.5
%U https://doi.org/10.18653/v1/2023.codi-1.5
%P 48-53
Markdown (Informal)
[Leveraging Structural Discourse Information for Event Coreference Resolution in Dutch](https://aclanthology.org/2023.codi-1.5) (De Langhe et al., CODI 2023)
ACL