Triple
T10604116
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McKenzie, Brackman, Chaney and Kuzak |
E275828
|
entity |
| Predicate | hasNameComponent |
P24447
|
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: [McKenzie, Brackman, Chaney and Kuzak, hasNameComponent, McKenzie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: McKenzie Context triple: [McKenzie, Brackman, Chaney and Kuzak, hasNameComponent, 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.
McKaley
McKaley is an American actress best known for her roles in television series such as "Hart of Dixie" and "Scream Queens."
-
D.
Mackenzell
Mackenzell is a small village in the Hesse region of central Germany.
-
E.
Keally
Keally is a surname most notably associated with Francis Keally, an American architect active in the early to mid-20th century.
- 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_69d6aaf948d88190806cc3a8c47a3fb2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d6df4992248190b640d743ccf02c82 |
completed | April 8, 2026, 11:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d95eaffcd0819098e0a06a731b602f |
completed | April 10, 2026, 8:33 p.m. |
Created at: April 8, 2026, 7:32 p.m.