Triple
T22234526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raoul Dufy |
E549555
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Raoul |
—
|
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: Raoul | Statement: [Raoul Dufy, givenName, Raoul]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Raoul Context triple: [Raoul Dufy, givenName, Raoul]
-
A.
Raoul
Raoul is a violent, masked intruder and one of the primary antagonists in the thriller film "Panic Room."
-
B.
Raoul
chosen
Raoul is a masculine given name of French origin, notably borne by the Fauvist painter Raoul Dufy.
-
C.
Raoul d’Harcourt
Raoul d’Harcourt was a French nobleman and ecclesiastic of the influential Harcourt family, known for his role in founding the medieval Collège d’Harcourt in Paris.
-
D.
Usuard of Saint-Germain
Usuard of Saint-Germain was a 9th-century Benedictine monk and hagiographer best known for compiling an influential martyrology that shaped the Western Church’s liturgical calendar.
-
E.
Gioffre
Gioffre is an Italian given name most notably borne by Gioffre Borgia, a younger son of Pope Alexander VI from the influential Borgia family of Renaissance Italy.
- 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_69e11e4102b881909cf47d3768e25c19 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12bf61504819093e70bee4c575d1c |
completed | April 28, 2026, 9:51 p.m. |
Created at: April 16, 2026, 8:38 p.m.