Triple
T7402816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Libre (fragrance) |
E170789
|
entity |
| Predicate | perfumer |
P39615
|
FINISHED |
| Object | Anne Flipo |
E542962
|
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: Anne Flipo | Statement: [Libre (fragrance), perfumer, Anne Flipo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anne Flipo Context triple: [Libre (fragrance), perfumer, Anne Flipo]
-
A.
Anne Flipo
chosen
Anne Flipo is a renowned French perfumer celebrated for creating numerous successful fragrances for major luxury brands.
-
B.
Jeannine Guillou
Jeannine Guillou was a French painter and the first wife and close artistic companion of the Russian-born French artist Nicolas de Staël.
-
C.
Suzanne Jolibois
Suzanne Jolibois was the wife of French phenomenologist and philosopher Maurice Merleau-Ponty.
-
D.
Irma Bécot
Irma Bécot is a character in Émile Zola’s novel "L’Œuvre," representing the Parisian demi-monde and the complex social milieu surrounding the struggling artist protagonists.
-
E.
Suzanne Ferrière
Suzanne Ferrière was a Swiss social worker and humanitarian known for her influential role in the International Committee of the Red Cross during the first half of the 20th century.
- 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_69c68a6010108190925e5284de022660 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f26ea27c8190a55e0e0314b463d8 |
completed | March 27, 2026, 9:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c81110d7648190a8938db7061be454 |
completed | March 28, 2026, 5:34 p.m. |
Created at: March 27, 2026, 3:10 p.m.