Triple
T2886934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Honoré Daumet |
E59528
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Honoré |
E71662
|
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: Honoré | Statement: [Honoré Daumet, givenName, Honoré]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Honoré Context triple: [Honoré Daumet, givenName, Honoré]
-
A.
Honoré
chosen
Honoré is the given name of the renowned 19th-century French novelist and playwright Honoré de Balzac.
-
B.
Antoine
Antoine is the given name of Antoine de la Mothe Cadillac, the French explorer and founder of Detroit.
-
C.
Henri
Henri is a given name most famously associated with the French artist Henri Matisse.
-
D.
Étienne
Étienne is the given first name of the French Symbolist poet Stéphane Mallarmé.
-
E.
Théodore
Théodore is a masculine given name of Greek origin, commonly used in French-speaking countries and borne by notable figures such as the Reformation theologian Théodore Beza.
- 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_69ab4ac739188190a112f42a5a69c951 |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abe0463ccc8190bf08330f40d0cfdc |
completed | March 7, 2026, 8:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b324d0152881909526cf9079560dc6 |
completed | March 12, 2026, 8:40 p.m. |
Created at: March 6, 2026, 10:03 p.m.