Triple
T15138112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Honorine |
E361609
|
entity |
| Predicate | relatedName |
P3889
|
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: [Honorine, relatedName, Honoré]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Honoré Context triple: [Honorine, relatedName, Honoré]
-
A.
Honoré
chosen
Honoré is the given name of the renowned 19th-century French novelist and playwright Honoré de Balzac.
-
B.
Maxime
Maxime is a French given name commonly used for males, derived from the Latin name Maximus meaning "greatest."
-
C.
Félicien
Félicien is a masculine given name of French origin, notably borne by the 19th-century Belgian artist and printmaker Félicien Rops.
-
D.
Ambroise
Ambroise is a modern digital revival of classic Didone-style typefaces, characterized by high contrast between thick and thin strokes and elegant, refined letterforms.
-
E.
Antoine
Antoine is the given name of Antoine de la Mothe Cadillac, the French explorer and founder of Detroit.
- 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_69d85a06450081909c5a14ea9851a15e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005b59b488190b0016970647e7483 |
completed | April 15, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff1a61136081908198806944c81808 |
completed | May 9, 2026, 11:28 a.m. |
Created at: April 10, 2026, 3:07 a.m.