Triple
T3047243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Winner Within: A Life Plan for Team Players |
E83478
|
entity |
| Predicate | usesAsExamples |
P41972
|
FINISHED |
| Object | NBA 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: NBA basketball | Statement: [The Winner Within: A Life Plan for Team Players, usesAsExamples, NBA basketball]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesAsExamples Context triple: [The Winner Within: A Life Plan for Team Players, usesAsExamples, NBA basketball]
-
A.
usedAsExampleIn
Indicates that one entity is cited or presented as an illustrative example within another entity, such as a text, discussion, or explanation.
-
B.
isUsedToIllustrate
chosen
Indicates that one entity serves as an example or demonstration to clarify, explain, or represent another entity.
-
C.
hasExample
Indicates that one entity serves as an instance, illustration, or concrete example of another entity.
-
D.
usedToExplain
Indicates that one entity serves as an explanation or clarification for another entity.
-
E.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
- 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_69ad8b24924c8190a9bb6f61d519e4ae |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9bad11b48190a5bd01e91a320e14 |
completed | March 8, 2026, 3:54 p.m. |
| PD | Predicate disambiguation | batch_69ad962195388190856013a2519c2b0f |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3:01 p.m.