TIME: A Multi-level Benchmark for Temporal Reasoning of LLMs in Real-World Scenarios
Introduction of TIME
Temporal reasoning is pivotal for Large Language Models (LLMs) to comprehend the real world. However, existing works neglect the real-world challenges for temporal reasoning: (1) intensive temporal information, (2) fast-changing event dynamics, and (3) complex temporal dependencies in social interactions. To bridge this gap, we propose a multi-level benchmark TIME, designed for temporal reasoning in real-world scenarios.
TIME consists of 38,522 QA pairs, covering 3 levels with 11 fine-grained sub-tasks. This benchmark encompasses 3 sub-datasets reflecting different real-world challenges: TIME-Wiki, TIME-News, and TIME-Dial. We conduct extensive experiments on reasoning models and non-reasoning models. And we conducted an in-depth analysis of temporal reasoning performance across diverse real-world scenarios and tasks, and summarized the impact of test-time scaling on temporal reasoning capabilities. Additionally, we release TIME-Lite, a human-annotated subset to foster future research and standardized evaluation in temporal reasoning.
Dataset Statistics
| Dataset | All Tasks | Ext. | Loc. | Comp. | D.C. | O.C. | E.R. | O.R. | R.R. | C.T. | T.L. | C.F. |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| TIME | 38522 | 1480 | 3546 | 3376 | 3401 | 3549 | 3537 | 3538 | 3537 | 3513 | 5508 | 3537 |
| TIME-Wiki | 13848 | 1261 | 1299 | 1126 | 1151 | 1299 | 1287 | 1288 | 1287 | 1263 | 1300 | 1287 |
| TIME-News | 19958 | 0 | 1800 | 1800 | 1800 | 1800 | 1800 | 1800 | 1800 | 1800 | 3758 | 1800 |
| TIME-Dial | 4716 | 219 | 447 | 450 | 450 | 450 | 450 | 450 | 450 | 450 | 450 | 450 |
| TIME-Lite | 943 | 60 | 90 | 78 | 86 | 90 | 90 | 90 | 90 | 90 | 89 | 90 |
| TIME-Lite-Wiki | 322 | 30 | 30 | 24 | 28 | 30 | 30 | 30 | 30 | 30 | 30 | 30 |
| TIME-Lite-News | 299 | 0 | 30 | 30 | 30 | 30 | 30 | 30 | 30 | 30 | 29 | 30 |
| TIME-Lite-Dial | 322 | 30 | 30 | 24 | 28 | 30 | 30 | 30 | 30 | 30 | 30 | 30 |
Task abbreviations: Ext. (Extract), Loc. (Localization), Comp. (Computation), D.C. (Duration Compare), O.C. (Order Compare); E.R. (Explicit Reasoning), O.R. (Order Reasoning), R.R. (Relative Reasoning); C.T. (Co-temporality), T.L. (Timeline), C.F. (Counterfactual).
Construction Pipeline
Evaluation Results
TIME-Lite Results Radar Charts
TIME-Lite-Wiki
TIME-Lite-News
TIME-Lite-Dial
Get Started
📥 Download Dataset
Option 1: Complete TIME Dataset
# Install git-lfs
pip install git-lfs
# Navigate to the working directory and download the benchmark dataset TIME
chmod +x scripts/download_data_time.sh
# Download the data
./scripts/download_data_time.shOption 2: TIME-Lite Dataset (Recommended)
# Navigate to the working directory and download the benchmark dataset TIME-Lite
chmod +x scripts/download_data_time_lite.sh
# Download the data
./scripts/download_data_time_lite.sh🔧 Installation
# Install dependencies
pip install -r evaluation/requirements.txt🚀 Evaluation
# Evaluate TIME dataset
./scripts/eval_time.sh
# Evaluate TIME-Lite dataset (Recommended)
./scripts/eval_time_lite.shCitation
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