BoschAI @ Causal News Corpus 2023: Robust Cause-Effect Span Extraction using Multi-Layer Sequence Tagging and Data Augmentation

December 11, 2023 ยท Declared Dead ยท ๐Ÿ› CASE

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Authors Timo Pierre Schrader, Simon Razniewski, Lukas Lange, Annemarie Friedrich arXiv ID 2312.06338 Category cs.CL: Computation & Language Cross-listed cs.AI Citations 2 Venue CASE Last Checked 4 months ago
Abstract
Understanding causality is a core aspect of intelligence. The Event Causality Identification with Causal News Corpus Shared Task addresses two aspects of this challenge: Subtask 1 aims at detecting causal relationships in texts, and Subtask 2 requires identifying signal words and the spans that refer to the cause or effect, respectively. Our system, which is based on pre-trained transformers, stacked sequence tagging, and synthetic data augmentation, ranks third in Subtask 1 and wins Subtask 2 with an F1 score of 72.8, corresponding to a margin of 13 pp. to the second-best system.
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