Triple
T20015046
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vivo per lei |
E494694
|
entity |
| Predicate | performedAsDuetWith |
P9649
|
FINISHED |
| Object | Hélène Ségara |
—
|
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: Hélène Ségara | Statement: [Vivo per lei, performedAsDuetWith, Hélène Ségara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hélène Ségara Context triple: [Vivo per lei, performedAsDuetWith, Hélène Ségara]
-
A.
Hélène Ségara
chosen
Hélène Ségara is a French pop singer and musical theatre performer best known internationally for playing Esmeralda in the hit stage musical Notre-Dame de Paris.
-
B.
Mireille Mathieu
Mireille Mathieu is a French chanteuse renowned for her powerful voice, classic chanson repertoire, and international success since the 1960s.
-
C.
Sylvie Vartan
Sylvie Vartan is a Bulgarian-born French pop singer and actress who became one of France’s most popular yé-yé idols in the 1960s.
-
D.
Laeticia Hallyday
Laeticia Hallyday is a French former model and philanthropist best known as the widow and longtime manager of rock icon Johnny Hallyday.
-
E.
Mylène Farmer
Mylène Farmer is a French singer-songwriter and producer renowned for her melancholic pop music, poetic lyrics, and visually striking, often controversial music videos.
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6623bba1881908440c92f08729ec1 |
completed | April 20, 2026, 5:28 p.m. |
Created at: April 11, 2026, 3:34 p.m.