Triple
T12119604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cavalier Johnson |
E288656
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Cavalier |
E288656
|
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: Cavalier | Statement: [Cavalier Johnson, givenName, Cavalier]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cavalier Context triple: [Cavalier Johnson, givenName, Cavalier]
-
A.
Cavalier
Cavalier is the costumed mascot character representing the University of Virginia’s athletic teams, typically depicted as a historical Virginia cavalryman.
-
B.
Cavalier
chosen
Cavalier is the first name of Cavalier Johnson, an American politician serving as the mayor of Milwaukee, Wisconsin.
-
C.
Cavalier
Cavalier was a mid-20th-century American men's magazine known for publishing fiction, including early works by notable authors such as Stephen King.
-
D.
Bassett
Bassett is the surname of acclaimed American actress and director Angela Bassett, known for her powerful performances in film and television.
-
E.
Philander Chase
Philander Chase was a 19th-century American Episcopal bishop and educator best known for establishing influential frontier colleges and promoting religious education in the Midwest.
- 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_69d6ab4a5c448190a110d1273314b21a |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91577a03c81909add7a5d7324a648 |
completed | April 10, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f682397c819085a86a98e079660b |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 8, 2026, 9:49 p.m.