Triple
T17518994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stochelo Rosenberg |
E426637
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object | Romane |
—
|
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: Romane | Statement: [Stochelo Rosenberg, associatedAct, Romane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Romane Context triple: [Stochelo Rosenberg, associatedAct, Romane]
-
A.
Romane
chosen
Romane is a French gypsy jazz guitarist and composer known for his modern take on the Django Reinhardt tradition.
-
B.
Romane
Romane is a French actress and filmmaker known for her roles in European cinema and her work in independent films.
-
C.
Romang
Romang is a remote volcanic island in Indonesia’s Maluku province, known for its rugged terrain, small coastal settlements, and location within the tectonically active Banda Sea region.
-
D.
Romanze
Romanze is a lyrical, song-like type of slow movement commonly used in classical concertos and chamber music to convey expressive, romantic character.
-
E.
Fotoromanza
Fotoromanza is a popular 1984 Italian pop-rock song by singer-songwriter Gianna Nannini that became one of her signature hits.
- 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_69d889dd9164819087b1dc3c9240c870 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e452d18c1c81908bb843bbddb44ca1 |
completed | April 19, 2026, 3:58 a.m. |
Created at: April 10, 2026, 5:49 a.m.