Triple
T17571534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sherrill Milnes |
E427950
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Sherrill |
—
|
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: Sherrill | Statement: [Sherrill Milnes, givenName, Sherrill]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sherrill Context triple: [Sherrill Milnes, givenName, Sherrill]
-
A.
Sherrill
chosen
Sherrill is a surname most prominently associated with Jackie Sherrill, a well-known American college football coach.
-
B.
Tilghman
Tilghman is a surname most notably associated with Shirley M. Tilghman, a prominent molecular biologist and former president of Princeton University.
-
C.
Tilghman
Tilghman is a masculine given name of English origin that has been borne by various notable American figures, including politicians and military officers.
-
D.
Alden
Alden is the given name of American actor Alden Ehrenreich, known for roles in films such as "Hail, Caesar!" and "Solo: A Star Wars Story."
-
E.
Alden
Alden is a small unincorporated community and popular lakeside resort area on the shores of Torch Lake in northern Michigan.
- 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_69d889e0385081908a04b66f4dd4bd0d |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e45930b0748190b55b95c523c47460 |
completed | April 19, 2026, 4:25 a.m. |
Created at: April 10, 2026, 5:50 a.m.