GDLLM improves event temporal relation extraction by feeding LLM-generated probability distributions into a graph attention network, achieving state-of-the-art micro-F1 scores on TB-Dense and MATRES.
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GDLLM: A Global Distance-aware Modeling Approach Based on Large Language Models for Event Temporal Relation Extraction
GDLLM improves event temporal relation extraction by feeding LLM-generated probability distributions into a graph attention network, achieving state-of-the-art micro-F1 scores on TB-Dense and MATRES.