Triple
T23559360
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whitman Mayo |
E579188
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Whitman Mayo |
—
|
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: Whitman Mayo | Statement: [Whitman Mayo, name, Whitman Mayo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Whitman Mayo Context triple: [Whitman Mayo, name, Whitman Mayo]
-
A.
Whitman Mayo
chosen
Whitman Mayo was an American character actor best known for his role as Grady Wilson on the television sitcom "Sanford and Son."
-
B.
Frederic H. Spaulding
Frederic H. Spaulding was an American educator and civic leader best known for establishing the University of Tampa in Florida.
-
C.
Charles H. Mayo
Charles H. Mayo was an American physician and co-founder of the Mayo Clinic, renowned for his contributions to modern medical practice and healthcare organization.
-
D.
Henry D. Minot
Henry D. Minot was a 19th-century American ornithologist and railroad executive whose contributions to both fields led to the naming of Minot, North Dakota in his honor.
-
E.
William B. Mayo
William B. Mayo was an American physician and medical leader best known as one of the founders of the American Cancer Society.
- 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_69e245fe24588190888f3aec8407d8e3 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1af672db4819087dbff2c0dfadd7f |
completed | April 29, 2026, 7:12 a.m. |
Created at: April 17, 2026, 6:12 p.m.