Triple
T23188566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony Kanaan |
E579665
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Antoine |
—
|
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: Antoine | Statement: [Tony Kanaan, givenName, Antoine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Antoine Context triple: [Tony Kanaan, givenName, Antoine]
-
A.
Antoine
chosen
Antoine is a French given name, historically common in Francophone countries and borne by numerous notable figures in politics, arts, and science.
-
B.
Antoine
Antoine is the given name of Antoine de la Mothe Cadillac, the French explorer and founder of Detroit.
-
C.
Antoine
Antoine is a character in Honoré de Balzac’s novel "The Wild Ass's Skin," appearing within its exploration of desire, fate, and the consequences of wish fulfillment.
-
D.
Antoine
Antoine is the given name of French naval officer and explorer Bruni d’Entrecasteaux, known for leading late 18th-century Pacific expeditions.
-
E.
Antoine
Antoine is the hapless, over-accommodating maître d’ whose attempts to please everyone drive the farcical chaos in the French comedy film "Après vous...".
- 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_69e245ff8000819090d12008805315b7 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18fd592248190a7e705c554885cd1 |
completed | April 29, 2026, 4:57 a.m. |
Created at: April 17, 2026, 4:05 p.m.