CMNIE: An Information Extraction Benchmark for Chinese Military News
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Abstract
CMNIE is a benchmark for structured extraction from Chinese military news, addressing the need for joint information extraction in this domain.
Reality Card
CMNIE provides a comprehensive dataset with 13,000 instances and unified annotations for event triggers, arguments, entities, and relations, facilitating improved information extraction in Chinese military news.
The dataset includes manual annotations for 7 event types, 10 argument roles, 7 entity types, and 8 relation types.
The challenge of exact matching of event-argument spans and the performance of zero-shot LLMs in identifying relevant semantic units without matching gold span boundaries.
Paper to code
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