Triple
T1220340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Homestead, Florida |
E26206
|
entity |
| Predicate | hazardExposure |
P1950
|
FINISHED |
| Object | hurricane-prone area |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: hurricane-prone area | Statement: [Homestead, Florida, hazardExposure, hurricane-prone area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hazardExposure Context triple: [Homestead, Florida, hazardExposure, hurricane-prone area]
-
A.
hazardScope
Indicates the range or extent within which a particular hazard is relevant, applicable, or has effect.
-
B.
hazardType
chosen
Indicates the specific kind or category of hazard associated with an entity or situation.
-
C.
hasNotableHazard
Indicates that an entity is associated with a significant risk, danger, or harmful condition that is noteworthy or exceptional.
-
D.
hasClimbingHazard
Indicates that something presents a risk or danger specifically associated with climbing activities.
-
E.
endangerment
Indicates a relationship in which one entity exposes another to potential harm, risk, or danger.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a49484688c8190a1bf285eb396a8b6 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4be1ead088190bf44dc6ab1edf18b |
completed | March 1, 2026, 10:30 p.m. |
| PD | Predicate disambiguation | batch_69a4bb644af08190ba25905f20adb01a |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:46 p.m.