Triple
T20230680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turkey Stearnes |
E495513
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Stearnes |
—
|
NE NERFINISHED |
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: Stearnes | Statement: [Turkey Stearnes, familyName, Stearnes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stearnes Context triple: [Turkey Stearnes, familyName, Stearnes]
-
A.
Stearnes
chosen
Stearnes is the surname of Turkey Stearnes, a Hall of Fame Negro Leagues baseball star known as one of the greatest power hitters of his era.
-
B.
O'Steen
O'Steen is a surname most notably associated with American film editor Sam O'Steen, known for his work on several acclaimed Hollywood films.
-
C.
Waitley
Waitley is a surname most notably associated with Denis Waitley, an American motivational speaker and self-help author.
-
D.
Estey
Estey is a surname and place name most commonly associated with North American families and locations, sometimes appearing as a variant spelling of similar names like Easty.
-
E.
Trulaske
Trulaske is the commonly used name for the Robert J. Trulaske, Sr. College of Business at the University of Missouri, a business school offering undergraduate and graduate programs in fields such as accounting, finance, and management.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da626cff80819097b530718a7c98b6 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66fdce9d081909752a6a1e15283ba |
completed | April 20, 2026, 6:26 p.m. |
Created at: April 11, 2026, 11:39 p.m.