Triple
T34439695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jewel Changi Airport |
E884062
|
entity |
| Predicate | rainVortexWaterfallType |
P36915
|
FINISHED |
| Object | indoor waterfall |
—
|
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: indoor waterfall | Statement: [Jewel Changi Airport, rainVortexWaterfallType, indoor waterfall]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rainVortexWaterfallType Context triple: [Jewel Changi Airport, rainVortexWaterfallType, indoor waterfall]
-
A.
typeOfWaterfall
chosen
Indicates that one entity is a specific kind or category of waterfall in relation to another entity.
-
B.
waterfallAlong
Indicates that a waterfall is located along the course, path, or extent of another geographic feature such as a river, trail, or boundary.
-
C.
waterfallName
Indicates that an entity is identified by or associated with the specific name of a waterfall.
-
D.
waterfallHeight
Indicates the vertical distance or drop in elevation from the top to the bottom of a waterfall.
-
E.
nearbyWaterfall
Indicates that the entity is located close to or within a short distance of a waterfall.
- 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_69f349c548d88190978e2a82502c03d0 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f719492e7c8190896aa9fc1d63708e |
completed | May 3, 2026, 9:45 a.m. |
| PD | Predicate disambiguation | batch_69f71824431081908d9685d2462ea242 |
completed | May 3, 2026, 9:40 a.m. |
Created at: May 1, 2026, 2 a.m.