Triple
T35479235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand Court |
E1025422
|
entity |
| Predicate | floorCountOpenThrough |
P183332
|
FINISHED |
| Object | several stories |
—
|
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: several stories | Statement: [Grand Court, floorCountOpenThrough, several stories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: floorCountOpenThrough Context triple: [Grand Court, floorCountOpenThrough, several stories]
-
A.
floorCount
Indicates the number of floors or levels that a building or structure has.
-
B.
floorAccess
Indicates that an entity is permitted to enter or use a specific floor or level within a building or structure.
-
C.
floorCountRange
Indicates the range between the minimum and maximum number of floors associated with an entity.
-
D.
floorCountAroundSpace
Indicates the number of floors present in the vicinity of a given space or area.
-
E.
floorCountApproximate
Indicates an approximate or estimated number of floors associated with a building or structure.
- F. None of above. chosen
Provenance (4 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_69f76dfadba0819083456aadcd6864ea |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79da9f80c8190b0afd8509f28747b |
completed | May 3, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69f79617d40481909ba372f94209c08b |
completed | May 3, 2026, 6:38 p.m. |
| PDg | Predicate description generation | batch_69f79da8d8848190ab5ab1bdad95d58c |
completed | May 3, 2026, 7:10 p.m. |
Created at: May 3, 2026, 4:04 p.m.