Conference paper Open Access

Multilingual Epidemic Event Extraction

Mutuvi, Stephen; Boros, Emanuela; Doucet, Antoine; Lejeune, Gaël; Jatowt, Adam; Odeo, Moses

In this paper, we focus on epidemic event extraction in multilingual and low-resource settings. The task of extracting epidemic events is defined as the detection of disease names and locations in a document. We experiment with a multilingual dataset comprising news articles from the medical domain with diverse morphological structures (Chinese, English, French, Greek, Polish, and Russian). We investigate various Transformer-based models, also adopting a two-stage strategy, first finding the documents that contain events and then performing event extraction. Our results show that error propagation to the downstream task was higher than expected. We also perform an in-depth analysis of the results, concluding that different entity characteristics can influence the performance. Moreover, we perform several preliminary experiments for the low-resourced languages present in the dataset using the mean teacher semi-supervised technique. Our findings show the potential of pre-trained language models benefiting from the incorporation of unannotated data in the training process.

Files (357.2 kB)
Name Size
Mutuvi.pdf
md5:e46d43e4d208980f7113ef04e0d67f13
357.2 kB Download
12
8
views
downloads
Views 12
Downloads 8
Data volume 2.9 MB
Unique views 9
Unique downloads 8

Share

Cite as