Triple
T16255238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kentucky Science Center |
E394610
|
entity |
| Predicate | buildingCount |
P11484
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Kentucky Science Center, buildingCount, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: buildingCount Context triple: [Kentucky Science Center, buildingCount, 3]
-
A.
numberOfBuildings
chosen
Indicates the total count of buildings associated with a given entity or within a specified context.
-
B.
towerCount
Indicates the number of towers associated with or present in a given entity or context.
-
C.
buildingStructure
Indicates that one entity is a structural component or physical part that forms, supports, or constitutes the construction of another entity.
-
D.
currentBuildings
Indicates that certain buildings are presently existing, active, or in use at a given time or context.
-
E.
building
Indicates that one entity constructs, assembles, or develops another entity, typically over a period of time.
- 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_69d87f2171208190951025e526947816 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e24599861881908b9235f005d80a96 |
completed | April 17, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69e219f259e88190bf49d8408c04178e |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:04 a.m.