Triple
T22943202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fern Grotto |
E569788
|
entity |
| Predicate | safetyEvents |
P113889
|
FINISHED |
| Object | damaged by Hurricane Iniki in 1992 |
—
|
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: damaged by Hurricane Iniki in 1992 | Statement: [Fern Grotto, safetyEvents, damaged by Hurricane Iniki in 1992]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyEvents Context triple: [Fern Grotto, safetyEvents, damaged by Hurricane Iniki in 1992]
-
A.
securityIncidents
Indicates that one or more security-related breaches, threats, or violations have occurred involving the referenced entities.
-
B.
safetyOutcome
Indicates the resulting condition or consequence related to safety that arises from an action, event, or situation.
-
C.
notableSafety
Indicates that an entity is recognized for having significant safety characteristics, performance, or impact relative to others.
-
D.
safetyPoints
Indicates a relationship where an entity is assigned or associated with a measure of safety, typically quantified as points reflecting its safety level or performance.
-
E.
incidentWith
chosen
Indicates that one entity is involved in, affected by, or associated with a particular incident or event together with another entity.
- 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_69e24590862c8190858f180ad302adab |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1819b65dc8190b9456346e7284ddf |
completed | April 29, 2026, 3:57 a.m. |
| PD | Predicate disambiguation | batch_69ef3b882e708190b0eb0c87021c75b8 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:45 p.m.