Triple
T793201
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NCAA women’s basketball |
E16959
|
entity |
| Predicate | ballSize |
P3186
|
FINISHED |
| Object | size 6 (28.5-inch) basketball |
—
|
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: size 6 (28.5-inch) basketball | Statement: [NCAA women’s basketball, ballSize, size 6 (28.5-inch) basketball]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ballSize Context triple: [NCAA women’s basketball, ballSize, size 6 (28.5-inch) basketball]
-
A.
ballType
chosen
Indicates the specific category or kind of ball associated with an entity.
-
B.
bodySize
Indicates the relative physical magnitude or scale of an entity’s body, such as how large or small it is.
-
C.
romSize
Indicates the amount of read-only memory (ROM) associated with an entity, typically measured as its storage capacity.
-
D.
driverDiameter
Indicates the size of the circular cross-section of a driver component, typically measured as the distance across its widest point.
-
E.
approximateDiameter
Indicates that one entity specifies the estimated or rough measurement of another entity’s diameter.
- 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_69a4936cb7448190914f5fe4b8d81607 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a79a3bbc81908d818c50a366b0f8 |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a510f61881909175d6d8719246cd |
completed | March 1, 2026, 8:44 p.m. |
Created at: March 1, 2026, 7:38 p.m.