Triple
T22552237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Cocke |
E557586
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Cocke |
—
|
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: Cocke | Statement: [John Cocke, familyName, Cocke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cocke Context triple: [John Cocke, familyName, Cocke]
-
A.
Cocke
chosen
Cocke is an English-language surname borne by various notable figures in American political and military history.
-
B.
Cockrel
Cockrel is a surname most notably associated with Detroit politician and former mayor Kenneth Cockrel Jr.
-
C.
Coker
Coker is a residential and commercial neighborhood located within the Surulere area of Lagos, Nigeria.
-
D.
Coker
Coker is a surname of English origin borne by various notable individuals across fields such as religion, politics, sports, and the arts.
-
E.
The Cobb
The Cobb is a historic stone harbor wall and breakwater in Lyme Regis, England, famed for its role in protecting the town and for its appearances in literature and film.
- 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_69e11e59db848190b4272ecd2b690ffd |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f7647208190a1aaebd083bf095a |
completed | April 29, 2026, 1:31 a.m. |
Created at: April 16, 2026, 8:52 p.m.