Triple
T29987781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heinen’s Downtown Cleveland (Cleveland Trust Rotunda) |
E761776
|
entity |
| Predicate | floorCountOfStoreArea |
P1514
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Heinen’s Downtown Cleveland (Cleveland Trust Rotunda), floorCountOfStoreArea, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: floorCountOfStoreArea Context triple: [Heinen’s Downtown Cleveland (Cleveland Trust Rotunda), floorCountOfStoreArea, 2]
-
A.
floorCount
chosen
Indicates the number of floors or levels that a building or structure has.
-
B.
floorCountApproximate
Indicates an approximate or estimated number of floors associated with a building or structure.
-
C.
floorCountAroundSpace
Indicates the number of floors present in the vicinity of a given space or area.
-
D.
hasFloorArea
Indicates that an entity possesses a specified amount of floor space as a measurable area.
-
E.
floorHeight
Indicates the vertical elevation or level at which a particular floor is positioned within a 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_69f2246851148190b8e76206db94b105 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f679173f38819089b99a9a98c9001f |
completed | May 2, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69f66ec9919881908a187bfc7c4df192 |
completed | May 2, 2026, 9:38 p.m. |
Created at: April 29, 2026, 6:37 p.m.