Triple
T8829150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tower City Center |
E210087
|
entity |
| Predicate | numberOfFloorsInTerminalTower |
P76776
|
FINISHED |
| Object | 52 |
—
|
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: 52 | Statement: [Tower City Center, numberOfFloorsInTerminalTower, 52]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfFloorsInTerminalTower Context triple: [Tower City Center, numberOfFloorsInTerminalTower, 52]
-
A.
numberOfFloors
Indicates the total count of distinct floor levels that a building or structure has.
-
B.
numberOfFloorsServed
Indicates the total count of distinct floors that are served or accessed by a given entity (such as an elevator or service system).
-
C.
storeysOfTallestTower
chosen
Indicates the number of storeys contained in the tallest tower associated with the given context or entity.
-
D.
numberOfElevators
Indicates the total count of elevators associated with a given entity or location.
-
E.
hasNumberOfElevatorBanks
Indicates the relationship specifying how many distinct elevator banks are present in or associated with a given 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_69ca8365b28081909e48e45e95dfc405 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc604c52a48190807e46c15e3c1558 |
completed | April 1, 2026, 12:01 a.m. |
| PD | Predicate disambiguation | batch_69cc5c23d08481908d8c9b0ad3d1dc00 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:47 p.m.