Triple
T7639065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NOSPR concert hall |
E172952
|
entity |
| Predicate | hasNumberOfStoreysAboveGround |
P1728
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [NOSPR concert hall, hasNumberOfStoreysAboveGround, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfStoreysAboveGround Context triple: [NOSPR concert hall, hasNumberOfStoreysAboveGround, 4]
-
A.
numberOfFloors
chosen
Indicates the total count of distinct floor levels that a building or structure has.
-
B.
hasGroundFloor
Indicates that a building or structure includes a ground-level floor as part of its layout or design.
-
C.
hasUpperFloor
Indicates that one entity possesses or includes an upper floor relative to another level or reference point.
-
D.
numberOfBasementLevels
Indicates the total count of basement levels associated with a given structure or property.
-
E.
floorCountOfSurroundingBuildings
Indicates the number of floors in the buildings that are located around or near a given reference building or area.
- 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_69c69952849881908fdcea7a93bfc307 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6facb14188190952de18fa2699784 |
completed | March 27, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e8cadc8190b7977fcd213954dd |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:57 p.m.