Triple
T22390187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Where We Are |
E553491
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Quiz & Larossi |
—
|
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: Quiz & Larossi | Statement: [Where We Are, producer, Quiz & Larossi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Quiz & Larossi Context triple: [Where We Are, producer, Quiz & Larossi]
-
A.
Quiz & Larossi
chosen
Quiz & Larossi are a music production and songwriting duo known for crafting pop and dance tracks for various international artists.
-
B.
Paoletti
Paoletti is an Italian surname, likely related etymologically or familiarly to the name Paolone.
-
C.
LoPizzo
LoPizzo is an Italian-origin surname most notably associated with Anna LoPizzo, a labor activist killed during the 1912 Lawrence textile strike in the United States.
-
D.
Razzoli
Razzoli is a small, rugged island in Italy’s Maddalena Archipelago, known for its wild landscapes, granite cliffs, and clear turquoise waters.
-
E.
Cruppi
Cruppi is a French surname most notably associated with Jean Cruppi, a prominent early 20th-century French politician and statesman.
- 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_69e11e4cf87c8190a1ff474daec326b7 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15859853c8190b849cb34a94106da |
completed | April 29, 2026, 1:01 a.m. |
Created at: April 16, 2026, 8:45 p.m.