Triple
T6715698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Peter McKenzie |
E153261
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | McKenzie |
E437052
|
NE 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: McKenzie | Statement: [Dan Peter McKenzie, familyName, McKenzie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: McKenzie Context triple: [Dan Peter McKenzie, familyName, McKenzie]
-
A.
McKenzie
chosen
McKenzie is a Scottish-origin surname commonly borne by people of Scottish and Irish heritage and widely used in English-speaking countries.
-
B.
McKenna
McKenna is a surname of Irish origin commonly borne by individuals of Gaelic heritage.
-
C.
Keoghan
Keoghan is an Irish surname most prominently associated with actor Barry Keoghan, known for his roles in films such as "The Banshees of Inisherin" and "Dunkirk."
-
D.
Myles
Myles is a masculine given name of English origin, historically associated with figures such as Mayflower military leader Myles Standish.
-
E.
Kenley
Kenley is a suburban district in South London known for its residential character and proximity to green spaces such as Kenley Common and the historic Kenley Aerodrome.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c68809b4608190a2509ddb5ab87f05 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d1246b748190aed94e8ab8625f7e |
completed | March 27, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c700993128819081614ccfa68d7320 |
completed | March 27, 2026, 10:11 p.m. |
Created at: March 27, 2026, 2:07 p.m.