Position-aware end-to-end cross-document event coreference resolution for Dutch
- Author
- Loic De Langhe (UGent) , Orphée De Clercq (UGent) and Veronique Hoste (UGent)
- Organization
- Project
- Abstract
- Natural language understanding entails the ability to comprehend the relations between various people, objects or events throughout one, or multiple, text(s). Event coreference resolution (ECR) is a discourse-based natural language processing (NLP) task which aims to link those textual events, be they real or fictional, that refer to the same conceptual event. In this paper, we introduce a novel end-to-end approach for cross-document ECR which combines expert-level positional knowledge and graph-based representations in order to create a memory-efficient and accurate system meant for the detection and resolution of events in large document collections. We make three fundamental architectural changes to a current state-of-the-art cross-document ECR system and show that our approach outperforms this earlier model (+ 4% CONLL F1) on a large Dutch ECR dataset. Moreover, we show through in-depth qualitative and quantitative analysis that our proposed approach consistently detects more relevant events and suffers notably less from the typical issues models exhibit when predicting coreference chains.
- Keywords
- Coreference Resolution, Discourse Processing, Events
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01K99FR2Y35A4E9D816RH9FE35
- MLA
- De Langhe, Loic, et al. “Position-Aware End-to-End Cross-Document Event Coreference Resolution for Dutch.” NATURAL LANGUAGE PROCESSING, vol. 13, 2025, doi:10.1016/j.nlp.2025.100184.
- APA
- De Langhe, L., De Clercq, O., & Hoste, V. (2025). Position-aware end-to-end cross-document event coreference resolution for Dutch. NATURAL LANGUAGE PROCESSING, 13. https://doi.org/10.1016/j.nlp.2025.100184
- Chicago author-date
- De Langhe, Loic, Orphée De Clercq, and Veronique Hoste. 2025. “Position-Aware End-to-End Cross-Document Event Coreference Resolution for Dutch.” NATURAL LANGUAGE PROCESSING 13. https://doi.org/10.1016/j.nlp.2025.100184.
- Chicago author-date (all authors)
- De Langhe, Loic, Orphée De Clercq, and Veronique Hoste. 2025. “Position-Aware End-to-End Cross-Document Event Coreference Resolution for Dutch.” NATURAL LANGUAGE PROCESSING 13. doi:10.1016/j.nlp.2025.100184.
- Vancouver
- 1.De Langhe L, De Clercq O, Hoste V. Position-aware end-to-end cross-document event coreference resolution for Dutch. NATURAL LANGUAGE PROCESSING. 2025;13.
- IEEE
- [1]L. De Langhe, O. De Clercq, and V. Hoste, “Position-aware end-to-end cross-document event coreference resolution for Dutch,” NATURAL LANGUAGE PROCESSING, vol. 13, 2025.
@article{01K99FR2Y35A4E9D816RH9FE35,
abstract = {{Natural language understanding entails the ability to comprehend the relations between various people, objects or events throughout one, or multiple, text(s). Event coreference resolution (ECR) is a discourse-based natural language processing (NLP) task which aims to link those textual events, be they real or fictional, that refer to the same conceptual event. In this paper, we introduce a novel end-to-end approach for cross-document ECR which combines expert-level positional knowledge and graph-based representations in order to create a memory-efficient and accurate system meant for the detection and resolution of events in large document collections. We make three fundamental architectural changes to a current state-of-the-art cross-document ECR system and show that our approach outperforms this earlier model (+ 4% CONLL F1) on a large Dutch ECR dataset. Moreover, we show through in-depth qualitative and quantitative analysis that our proposed approach consistently detects more relevant events and suffers notably less from the typical issues models exhibit when predicting coreference chains.}},
articleno = {{100184}},
author = {{De Langhe, Loic and De Clercq, Orphée and Hoste, Veronique}},
issn = {{2977-0424}},
journal = {{NATURAL LANGUAGE PROCESSING}},
keywords = {{Coreference Resolution,Discourse Processing,Events}},
language = {{eng}},
pages = {{17}},
title = {{Position-aware end-to-end cross-document event coreference resolution for Dutch}},
url = {{http://doi.org/10.1016/j.nlp.2025.100184}},
volume = {{13}},
year = {{2025}},
}
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