arXiv Open Access 2022

Causality Detection using Multiple Annotation Decisions

Quynh Anh Nguyen Arka Mitra

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Abstrak

The paper describes the work that has been submitted to the 5th workshop on Challenges and Applications of Automated Extraction of socio-political events from text (CASE 2022). The work is associated with Subtask 1 of Shared Task 3 that aims to detect causality in protest news corpus. The authors used different large language models with customized cross-entropy loss functions that exploit annotation information. The experiments showed that bert-based-uncased with refined cross-entropy outperformed the others, achieving a F1 score of 0.8501 on the Causal News Corpus dataset.

Topik & Kata Kunci

cs.CL

Penulis (2)

Quynh Anh Nguyen

Arka Mitra

Format Sitasi

APA MLA BibTeX

Nguyen, Q.A., Mitra, A. (2022). Causality Detection using Multiple Annotation Decisions. https://arxiv.org/abs/2210.14852

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Informasi Jurnal

Tahun Terbit: 2022
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓