Triple
T21459321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Splish Splash water park |
E529427
|
entity |
| Predicate | hasFirstAidStation |
P51011
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Splish Splash water park, hasFirstAidStation, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFirstAidStation Context triple: [Splish Splash water park, hasFirstAidStation, true]
-
A.
hasAidStations
chosen
Indicates that one entity provides or contains aid or support stations for another entity or within a specified context.
-
B.
hasFireStation
Indicates that a location or area contains or is served by a fire station.
-
C.
hasTraumaCenter
Indicates that an entity (such as a hospital or facility) includes or is equipped with a designated trauma center capable of providing specialized emergency care for severe injuries.
-
D.
hasLifeboatStation
Indicates that a place or facility is equipped with a lifeboat station for maritime rescue or emergency response.
-
E.
hasImmediateMedicalResponse
Indicates that an entity receives prompt medical attention or intervention immediately following an incident or onset of a medical condition.
- 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_69e0c458133481908ae8b41a12c4edec |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9ed36c08190a5178b2308aca8da |
completed | April 23, 2026, 9:44 a.m. |
| PD | Predicate disambiguation | batch_69e631df1b38819088d3604854e697b4 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:08 p.m.