Triple
T13171508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don McCafferty |
E312986
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | McCafferty |
E312986
|
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: McCafferty | Statement: [Don McCafferty, familyName, McCafferty]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: McCafferty Context triple: [Don McCafferty, familyName, McCafferty]
-
A.
McFadden
McFadden is a surname most prominently associated with American actress and choreographer Gates McFadden, known for her role as Dr. Beverly Crusher in Star Trek: The Next Generation.
-
B.
Rafferty
Rafferty is an English model and actor best known as the son of actor Jude Law and actress Sadie Frost.
-
C.
Mulcahy
Mulcahy is an Irish surname of Gaelic origin, borne by various notable figures in Ireland and the Irish diaspora.
-
D.
Max McCaffrey
Max McCaffrey is an American former NFL wide receiver who played college football at Duke and had brief stints with several professional teams.
-
E.
Don McCafferty
chosen
Don McCafferty was an American football coach best known for leading the Baltimore Colts to victory in Super Bowl V.
- 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_69d806ac3ee081909b2fd27d060aa974 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98c2f22b881908a0af3af0a0af971 |
completed | April 10, 2026, 11:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6eafb81288190a6dcc3bd872998d8 |
completed | May 3, 2026, 6:28 a.m. |
Created at: April 9, 2026, 9:13 p.m.