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Urban Event Chains — Chicago, NYC, San Francisco

Data and results for Multi-Agent Prompting with In-Context Feedback for Cross-Modal Urban Event Chain Prediction (Sensors, MDPI).

Code: github.com/bibekgupta3333/urban-event-chain-prediction-multi-agent-prompting

Layout

Path Contents
chicago/, nyc/, sf/ Raw and daily-aligned city data (311, crime/incidents, collisions/crashes, permits, street closures, weather, traffic speed). Files with a _2022_2026 suffix cover 2022–2026; unsuffixed files are the original pull.
splits/ Chronological train / val / test splits and feature parquet files per city
chains/ Derived storm-triggered event chains with strong/weak labels ({city}_chains.jsonl)
rag/ Per-city retrieval documents and Chroma index (retrieval is not used in the reported experiments)
results/baseline/ 7 traditional baselines × 3 cities, per-chain predictions and metric summaries
results/{run_id}/{city}/{config}/{level}.jsonl Per-chain LLM agent predictions with .meta.json run manifests
results/runs/ Small pipeline smoke runs (1–2 chains, qwen3:0.6b) — pipeline evidence only, not cited

The nine *-bedrock-* run directories are the model grid the paper reports: 5 configurations (single_agent, multi_agent, noisy_single, multi_feedback, multi_no_feedback) × expert prompt level × 3 cities, 85 test chains per configuration. Bedrock exposes no seed, so these runs are not byte-reproducible.

Data notes

  • Traffic data are municipal traffic-speed feeds (probe-derived segment estimates, daily) — Chicago Traffic Tracker (sxs8-h27x), NYC Real-Time Traffic Speed (i4gi-tjb9), SF via DataSF. They carry no flow or occupancy and cover arterial roads.
  • Missing traffic days are empty/NaN, not zero. Never treat absent days as 0 mph.
  • chains/summary.json and rag/metadata.json are omitted because they are stale; recompute from the .jsonl files.

Sources and license

All raw data come from public city open-data portals (Chicago Data Portal, NYC Open Data, DataSF) and public weather records, and remain under those portals' terms. Derived files and results are released for research use.

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