Loic De Langhe


2023

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Leveraging Structural Discourse Information for Event Coreference Resolution in Dutch
Loic De Langhe | Orphee De Clercq | Veronique Hoste
Proceedings of the 4th Workshop on Computational Approaches to Discourse (CODI 2023)

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\%) and a minor improvement for cross-document settings (+ 1.1\%).

2022

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Investigating Cross-Document Event Coreference for Dutch
Loic De Langhe | Orphee De Clercq | Veronique Hoste
Proceedings of the Fifth Workshop on Computational Models of Reference, Anaphora and Coreference

In this paper we present baseline results for Event Coreference Resolution (ECR) in Dutch using gold-standard (i.e non-predicted) event mentions. A newly developed benchmark dataset allows us to properly investigate the possibility of creating ECR systems for both within and cross-document coreference. We give an overview of the state of the art for ECR in other languages, as well as a detailed overview of existing ECR resources. Afterwards, we provide a comparative report on our own dataset. We apply a significant number of approaches that have been shown to attain good results for English ECR including feature-based models, monolingual transformer language models and multilingual language models. The best results were obtained using the monolingual BERTje model. Finally, results for all models are thoroughly analysed and visualised, as to provide insight into the inner workings of ECR and long-distance semantic NLP tasks in general.