Triple
T21584040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Par les paupières |
E532598
|
entity |
| Predicate | performer |
P1363
|
FINISHED |
| Object | Alizée |
—
|
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: Alizée | Statement: [Par les paupières, performer, Alizée]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alizée Context triple: [Par les paupières, performer, Alizée]
-
A.
Alizée
chosen
Alizée is a French pop singer and dancer who rose to international fame in the early 2000s with her hit single "Moi... Lolita."
-
B.
Natacha St-Pier
Natacha St-Pier is a Canadian francophone pop singer known for her successful career in the French-speaking music world, including representing France at the Eurovision Song Contest in 2001.
-
C.
Angèle
Angèle is a Belgian pop singer-songwriter known for her witty, socially aware lyrics and hit songs like "Balance ton quoi."
-
D.
Axelle Francine
Axelle Francine is a French journalist and image consultant best known for her previous marriage to NBA star Tony Parker.
-
E.
Louane
Louane is a French singer and actress known for her pop hits and her breakout role in the film "La Famille Bélier."
- 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_69e0c4618bec8190bcb0feb74568cbb1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69eeeb5f2cc0819095552de70eb2ad8d |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 16, 2026, 6:31 p.m.