Triple
T22051689
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philippe Noiret |
E544899
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Noiret |
—
|
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: Noiret | Statement: [Philippe Noiret, familyName, Noiret]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Noiret Context triple: [Philippe Noiret, familyName, Noiret]
-
A.
Noiret
chosen
Noiret is a French surname most notably associated with acclaimed actor Philippe Noiret.
-
B.
Cottévrard
Cottévrard is a small commune in the Seine-Maritime department of the Normandy region in northern France.
-
C.
Loiseau
Loiseau is a French surname most notably borne by Gustave Loiseau, a post-Impressionist painter known for his landscapes and depictions of rural France.
-
D.
Chevreuse
Chevreuse is a historic town in north-central France known for its picturesque setting in the Chevreuse Valley and its medieval Château de la Madeleine.
-
E.
Tignère
Tignère is a town and commune located in Cameroon's Adamawa Region, known for its highland setting and role as a local administrative and trading center.
- 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_69e11e32445c8190ab97089b48a130bb |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1285513fc8190b691e1f57085956f |
completed | April 28, 2026, 9:36 p.m. |
Created at: April 16, 2026, 8:26 p.m.