NorEventGen: generative event extraction from Norwegian news

In this work, we approach event extraction from Norwegian news text using a generation-based approach which formulates the task as text-to-structure generation. We present experiments assessing the effect of different modeling configurations and provide an analysis of the model predictions and typical system errors. Finally, we apply our system to a large corpus of raw news texts and analyze the resulting distribution of event structures in a fairly representative snap-shot of the Norwegian news landscape.

Publication Details

Journal
DSpace repository (University of Tartu)
Published
2025-02-19
Primary Topic
Topic Modeling
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article
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article

NorEventGen: generative event extraction from Norwegian news

DSpace repository (University of Tartu)
Topic Modeling
article

NorEventGen: generative event extraction from Norwegian news

article en

Abstract

In this work, we approach event extraction from Norwegian news text using a generation-based approach which formulates the task as text-to-structure generation. We present experiments assessing the effect of different modeling configurations and provide an analysis of the model predictions and typical system errors. Finally, we apply our system to a large corpus of raw news texts and analyze the resulting distribution of event structures in a fairly representative snap-shot of the Norwegian news landscape.

DSpace repository (University of Tartu)
Openalex Percentile: Top 72%
Topic Modeling
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NorEventGen: generative event extraction from Norwegian news · DSpace repository (University of Tartu) (2025) | TGRS Research Map | TGRS