Datasetpublic

gabrielsunhyuck/IALA_B

IALA_B: Daytime, Single‑Mark JSON→JSON Dataset (1,500 samples) Input = VLM observation JSON (body/topmark attributes; may include synonyms/unknown).Output = LLM normalized JSON (mark_type, safe_direction, hazards, consistency, finalized_attributes…).Lateral mapping assumes IALA‑B (red=starboard, green=port). Total samples: 1500 Classes (9): cardinal_east, isolated_danger, lateral_port, lateral_starboard, cardinal_north, safe_water, cardinal_south, special_mark, cardinal_west… See the full description on the dataset page: https://huggingface.co/datasets/gabrielsunhyuck/IALA_B.

sourceHugging Facecc-by-4.0updated 11mo agoView on Hugging Face

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Dataset Card

IALA_B: Daytime, Single‑Mark JSON→JSON Dataset (1,500 samples)

Input = VLM observation JSON (body/topmark attributes; may include synonyms/unknown). Output = LLM normalized JSON (marktype, safedirection, hazards, consistency, finalized_attributes…). Lateral mapping assumes IALA‑B (red=starboard, green=port).

—Total samples: 1500
—Classes (9): cardinaleast, isolateddanger, lateralport, lateralstarboard, cardinalnorth, safewater, cardinalsouth, specialmark, cardinal_west
—Input augmentation: synonyms for topmark shapes (e.g., cone-shaped ≈ conical; circular ≈ circle; spheres/balls; apex‑to‑apex ≈ peak to peak).
—Outputs are normalized to a fixed vocabulary; conflicting/unknown inputs are downgraded to unknown in finalized_attributes and recorded in consistency.flagged_inconsistent.

Schema

User (input)

json

{
  "version": "v1",
  "context": { "time_of_day": "day", "region": "IALA-B" },
  "observation": {
    "body_color":    { "value": "<string>", "conf": <float> },
    "topmark_color": { "value": "<string|unknown>", "conf": <float> },
    "topmark_shape": { "value": "<string|unknown>", "conf": <float> }
  }
}

Assistant (output)

json

{
  "mark_type": "<enum>",
  "safe_direction": "<str>",
  "hazards": "<str>",
  "consistency": {
    "used_signals": ["..."],
    "flagged_inconsistent": ["..."],
    "notes": "<str>"
  },
  "finalized_attributes": {
    "body_color": "(...|unknown)",
    "topmark_color": "(...|unknown)",
    "topmark_shape": "(...|unknown)"
  },
  "confidence": <float>,
  "rules_applied": ["..."]
}

Loading

python

from datasets import load_dataset
ds = load_dataset("json", data_files={
    "train": "train.jsonl",
    "validation": "validation.jsonl"
})
print(ds)