Triple
T34495539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kai Tak Cruise Terminal |
E885595
|
entity |
| Predicate | terminalBuildingFloors |
P1514
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Kai Tak Cruise Terminal, terminalBuildingFloors, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: terminalBuildingFloors Context triple: [Kai Tak Cruise Terminal, terminalBuildingFloors, 3]
-
A.
numberOfFloors
Indicates the total count of distinct floor levels that a building or structure has.
-
B.
skyLobbyFloors
Indicates that the specified floors in a building function as sky lobbies, serving as intermediate transfer or lobby levels above the ground floor.
-
C.
locatedInBuildingFloorCount
Indicates that one entity is located in or associated with a building characterized by a specific number of floors.
-
D.
floorCount
chosen
Indicates the number of floors or levels that a building or structure has.
-
E.
occupiesFloorsOf
Indicates that one entity uses or takes up multiple levels or stories within a building or structure.
- 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_69f349cafcec8190997b45b3fdc16c27 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fb3425666081908916fcbf3b5dd907 |
completed | May 6, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_69fb2f5f3164819099429c2cc3d24e01 |
completed | May 6, 2026, 12:09 p.m. |
Created at: May 1, 2026, 2:01 a.m.