Triple
T1001174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indiana Pacers (ABA) |
E21604
|
entity |
| Predicate | jerseyFeature |
P22164
|
FINISHED |
| Object | ABA red, white and blue basketball usage |
—
|
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: ABA red, white and blue basketball usage | Statement: [Indiana Pacers (ABA), jerseyFeature, ABA red, white and blue basketball usage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: jerseyFeature Context triple: [Indiana Pacers (ABA), jerseyFeature, ABA red, white and blue basketball usage]
-
A.
jersey
Indicates that one entity is the jersey (sports uniform top) associated with, worn by, or representing another entity.
-
B.
jerseySignificance
Indicates the importance, meaning, or symbolic value associated with a particular jersey in a given context.
-
C.
jerseySecondaryColor
Indicates the secondary or accent color used on an entity’s jersey.
-
D.
jerseyColorMountainsClassification
Indicates a classification relationship that assigns or associates a jersey color with a specific mountains-related category or ranking.
-
E.
supportsFeature
Indicates that one entity provides, enables, or is compatible with a particular feature or capability of another.
- 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_69a493c53e648190ae8cb76c433fd9a7 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4fb18b88190ae2d620aaaff4f90 |
completed | March 1, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69a4b2b1f4f88190822598cfd2a0fd2b |
completed | March 1, 2026, 9:42 p.m. |
| PDg | Predicate description generation | batch_69a4b36064a48190b85c402f32cbadd1 |
completed | March 1, 2026, 9:45 p.m. |
Created at: March 1, 2026, 7:41 p.m.