Triple
T8155603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Celine Buckens |
E190441
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Celine |
E143077
|
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: Celine | Statement: [Celine Buckens, givenName, Celine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Celine Context triple: [Celine Buckens, givenName, Celine]
-
A.
Celine
Celine is a French luxury fashion house known for its minimalist, modern designs in ready-to-wear, leather goods, and accessories.
-
B.
Céline
chosen
Céline is the French given name of internationally renowned Canadian singer Céline Dion.
-
C.
Cami
Cami is a diminutive or nickname commonly used for the given name Camille.
-
D.
Fleurie
Fleurie is a renowned Beaujolais cru appellation in eastern France, celebrated for its elegant, floral Gamay-based red wines.
-
E.
Cécile
Cécile is the sensitive and central protagonist of the French film "Cible émouvante," around whom the story’s emotional and narrative developments revolve.
- 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_69ca82bfeb6481909d07b91b5cf69f59 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb44d725b88190b77dc7537c1fa95d |
completed | March 31, 2026, 3:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccbf0f68c88190be9aab03de6bf4a0 |
completed | April 1, 2026, 6:45 a.m. |
Created at: March 30, 2026, 5:37 p.m.