Temporal Reasoning Benchmark

该数据集是一个全面的基础评估工具，涵盖了广泛的时间粒度，旨在系统地评估大型语言模型在可解释时间推理方面的能力。此外，该数据集用于评估大型语言模型在预测和解释方面的性能，使用了包括精确度、召回率、F1分数、BLEU、ROUGE、METEOR和BERTScore在内的多种评价指标。这项任务的目的是对可解释的时间推理进行评估。

This dataset is a comprehensive foundational evaluation tool covering a wide range of temporal granularities, aiming to systematically assess the capabilities of large language models (LLMs) in interpretable temporal reasoning. Additionally, this dataset is used to evaluate the performance of large language models in prediction and explanation, adopting multiple evaluation metrics including precision, recall, F1 score, BLEU, ROUGE, METEOR, and BERTScore. The objective of this task is to assess interpretable temporal reasoning.