Triple
T12734529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shinjuku Sumitomo Building |
E304328
|
entity |
| Predicate | hasNumberOfFloorsAboveGround |
P78480
|
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: [Shinjuku Sumitomo Building, hasNumberOfFloorsAboveGround, 52]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfFloorsAboveGround Context triple: [Shinjuku Sumitomo Building, hasNumberOfFloorsAboveGround, 52]
-
A.
hasFloorsAboveGround
chosen
Indicates that an entity (typically a building or structure) possesses a specified number of floors that are located above ground level.
-
B.
numberOfFloors
Indicates the total count of distinct floor levels that a building or structure has.
-
C.
hasUpperFloor
Indicates that one entity possesses or includes an upper floor relative to another level or reference point.
-
D.
hasGroundFloor
Indicates that a building or structure includes a ground-level floor as part of its layout or design.
-
E.
floorCount
Indicates the number of floors or levels that a building or structure has.
- 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_69d7bdf1426c8190a4402e1c4cdec33a |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96d89ea70819098c470344f172167 |
completed | April 10, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69d96403957c81909acdee7bdae71696 |
completed | April 10, 2026, 8:56 p.m. |
Created at: April 9, 2026, 5:26 p.m.