Triple
T1483572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bora wind |
E29412
|
entity |
| Predicate | notableHazard |
P16293
|
FINISHED |
| Object | damage to infrastructure along the Adriatic coast |
—
|
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: damage to infrastructure along the Adriatic coast | Statement: [Bora wind, notableHazard, damage to infrastructure along the Adriatic coast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableHazard Context triple: [Bora wind, notableHazard, damage to infrastructure along the Adriatic coast]
-
A.
hasNotableHazard
chosen
Indicates that an entity is associated with a significant risk, danger, or harmful condition that is noteworthy or exceptional.
-
B.
hazardType
Indicates the specific kind or category of hazard associated with an entity or situation.
-
C.
notableFire
Indicates that a significant or historically important fire event is associated with the subject.
-
D.
hazardScope
Indicates the range or extent within which a particular hazard is relevant, applicable, or has effect.
-
E.
notableProtectiveFailure
Indicates a relationship where an entity’s protective role or safeguards significantly failed, leading to a notable or consequential breakdown in protection.
- 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_69a498da82e08190ba833330d05f380f |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c679714c8190ac53630fb49e19c5 |
completed | March 1, 2026, 11:06 p.m. |
| PD | Predicate disambiguation | batch_69a4c486eacc81909c272f9bdf50a7c3 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:12 p.m.