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GermEval2024 Shared Task 1 Subtask 1

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

하위 태스크
0
평가표
1
보존된 평가 기록
1

GermEval 2024 Shared Task 1 Subtask 1 involves predicting sexism labels for online comments based on human annotations that assess the strength of sexism or misogyny. Different strategies are used to derive the final label from multiple annotator inputs, such as majority voting or considering disagreement among annotators.

데이터셋

출처에 같은 태스크 이름으로 연결된 데이터셋입니다. 동명 태스크가 포함될 수 있으므로, 비교할 때는 평가 결과의 조건도 확인하세요.

GerMS-AT

This dataset contains 7984 user comments from an Austrian online newspaper. The comments have been annotated by 4 or more out of 11 annotators as to how strong sexism/mysogyny is present in the comment. It was used in the GermEval 2024 Shared Task 1: GerMS-Detect to evaluate data-driven approaches to automatically detect sexism in user comments. The dataset was introduced and described in Brigitte Krenn, Johann Petrak, Marina Kubina, and Christian Burger. 2024. Germs-at: A sexism/misogyny dataset of forum comments from an Austrian online newspaper. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 7728–7739. The data can be downloaded here: https://huggingface.co/datasets/ofai/GerMS-AT

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