Triple
T9728591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue |
E235677
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Eiffel 65 |
E817461
|
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: Eiffel 65 | Statement: [Blue, producer, Eiffel 65]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eiffel 65 Context triple: [Blue, producer, Eiffel 65]
-
A.
Eiffel 65
chosen
Eiffel 65 is an Italian Eurodance music group best known internationally for their late-1990s hit single "Blue (Da Ba Dee)."
-
B.
Alizée
Alizée is a French pop singer and dancer who rose to international fame in the early 2000s with her hit single "Moi... Lolita."
-
C.
Inna
Inna is a Romanian dance-pop singer known for international hits like "Hot" and "Sun Is Up."
-
D.
Lara Fabian
Lara Fabian is a Belgian-Canadian singer and songwriter renowned for her powerful vocals and emotive pop ballads in multiple languages, especially French.
-
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 (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_69ca84d0fad481909cdd45aa77416c48 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9eafa3a88190bc62924d94b89cd8 |
completed | April 1, 2026, 10:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1bcc8d2288190b2a1dc3fe1185030 |
completed | April 5, 2026, 1:37 a.m. |
Created at: March 30, 2026, 8:21 p.m.