Guided Distant Supervision for Multilingual Relation Extraction Data: Adapting to a New Language

Alistair Plum, Tharindu Ranasinghe, Christoph Purschke

Abstract
Relation extraction is essential for extracting and understanding biographical information in the context of digital humanities and related subjects. There is a growing interest in the community to build datasets capable of training machine learning models to extract relationships. However, annotating such datasets can be expensive and time-consuming, in addition to being limited to English. This paper applies guided distant supervision to create a large biographical relationship extraction dataset for German. Our dataset, composed of more than 80,000 instances for nine relationship types, is the largest biographical German relationship extraction dataset. We also create a manually annotated dataset with 2000 instances to evaluate the models and release it together with the dataset compiled using guided distant supervision. We train several state-of-the-art machine learning models on the automatically created dataset and release them as well. Furthermore, we experiment with multilingual and cross-lingual zero-shot experiments that could benefit many low-resource languages.
Anthology ID:
2024.lrec-main.703
Volume:
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Month:
May
Year:
2024
Address:
Torino, Italia
Editors:
Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
Venues:
LREC | COLING
SIG:
Publisher:
ELRA and ICCL
Note:
Pages:
7982–7992
Language:
URL:
https://aclanthology.org/2024.lrec-main.703
DOI:
Bibkey:
Cite (ACL):
Alistair Plum, Tharindu Ranasinghe, and Christoph Purschke. 2024. Guided Distant Supervision for Multilingual Relation Extraction Data: Adapting to a New Language. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 7982–7992, Torino, Italia. ELRA and ICCL.
Cite (Informal):
Guided Distant Supervision for Multilingual Relation Extraction Data: Adapting to a New Language (Plum et al., LREC-COLING 2024)
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https://preview.aclanthology.org/nschneid-patch-4/2024.lrec-main.703.pdf
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