Triple
T20370394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BB&T Center |
E497034
|
entity |
| Predicate | hasSuiteLevel |
P139885
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [BB&T Center, hasSuiteLevel, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSuiteLevel Context triple: [BB&T Center, hasSuiteLevel, yes]
-
A.
containsSuite
Indicates that one entity includes or encompasses a suite (a set or collection of related items, components, or units) as part of its contents.
-
B.
hasLevel
Indicates that an entity possesses or is associated with a particular degree, rank, or stage within an ordered scale or hierarchy.
-
C.
partOfSuite
Indicates that one item is a component or module belonging to a larger suite or collection.
-
D.
testSuite
Indicates that one entity is a collection or grouping of tests designed to be executed together, typically to validate behavior or functionality.
-
E.
numberOfSuites
Indicates the total count of suites associated with or contained within a given entity.
- 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_69e0b4a4f9b081908a5a021919c21ccb |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e678758b98819082c6440e03ad1615 |
completed | April 20, 2026, 7:03 p.m. |
| PD | Predicate disambiguation | batch_69e57648be3c81908256838228cabf5c |
completed | April 20, 2026, 12:41 a.m. |
| PDg | Predicate description generation | batch_69e58d7481508190a87c8b88f9df9879 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:26 a.m.