Multi-Turn Calendar Scheduling Conversations with Constraints

Nemotron Rl Instruction Following Calendar V2 is a multi-turn conversation dataset for understanding natural language scheduling constraints and inferring conflicts. It contains events with specific duration and timing constraints mentioned in random conversational order. The dataset was created by NVIDIA and last updated in March 2026.

Use Cases

• Train a conversational AI model to parse natural language duration and timing constraints for event scheduling.
• Develop a constraint satisfaction system that identifies scheduling conflicts from multi-turn user conversations.
• Fine-tune instruction-following models to handle multiple simultaneous constraints mentioned in random order.

Strengths

• Dataset focuses on multi-turn conversations, a complex format for training dialogue agents.
• Contains specific event constraints like duration and timing for realistic scheduling scenarios.
• Created by NVIDIA, a major organization in AI research and development.

Limitations

• Unknown dataset size, row count, and column structure prevents assessment of scale and feature richness.
• Sample data and file formats are unavailable, making initial inspection and integration planning difficult.
• Potential for synthetic or narrow conversational patterns, limiting generalizability to real-world user interactions.

Provenance

Source

huggingface

Freshness

Last updated March 2026.