Triple
T21935336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Real Hasta la Muerte |
E541671
|
entity |
| Predicate | hasProducer |
P30366
|
FINISHED |
| Object | Mambo Kingz |
—
|
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: Mambo Kingz | Statement: [Real Hasta la Muerte, hasProducer, Mambo Kingz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mambo Kingz Context triple: [Real Hasta la Muerte, hasProducer, Mambo Kingz]
-
A.
Mambo Kingz
chosen
Mambo Kingz is a Latin music production duo known for crafting reggaeton and urban hits for top artists in the Spanish-speaking music scene.
-
B.
Mambo
Mambo was the royal title used for the supreme ruler of the Rozvi Empire in what is now Zimbabwe.
-
C.
Mambo
Mambo is an open-source content management system that was widely used in the early 2000s for building dynamic websites and later served as the codebase origin for Joomla!.
-
D.
Mambo Kings
Mambo Kings is a 1992 musical drama film about two Cuban brothers pursuing a Latin music career in 1950s New York City.
-
E.
Kingmambo
Kingmambo was a champion Thoroughbred racehorse and highly influential sire known for producing numerous top-class runners worldwide.
- 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_69e0c47e2e5c81909a7f74ce3de50911 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f124048fe48190987340d5a6945176 |
completed | April 28, 2026, 9:17 p.m. |
Created at: April 16, 2026, 7:52 p.m.