Triple
T24955003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KRDG |
E624447
|
entity |
| Predicate | hasRescueAndFirefighting |
P127488
|
FINISHED |
| Object | airport fire services |
—
|
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: airport fire services | Statement: [KRDG, hasRescueAndFirefighting, airport fire services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRescueAndFirefighting Context triple: [KRDG, hasRescueAndFirefighting, airport fire services]
-
A.
hasFireRescueService
chosen
Indicates that an entity is served by, or responsible for providing, a fire and rescue service.
-
B.
hasFireAndRescueServiceCategory
Indicates the specific fire and rescue service classification or category assigned to an entity, such as a building, facility, or site.
-
C.
fireRescue
Indicates a relationship where one entity performs or is responsible for rescuing people or property from fires or fire-related emergencies involving another entity.
-
D.
hasFireServicesFrom
Indicates that one entity receives fire protection or firefighting services from another entity.
-
E.
hasFireExtinguishers
Indicates that the subject is equipped with or possesses one or more fire extinguishers.
- 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_69e2ff23a3a88190b1b9743fe5e15f94 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f67f0488bc819089fbd2d2478158d3 |
completed | May 2, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69f67e3ed894819094c067c1ef624951 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 18, 2026, 5:57 a.m.