Triple

T18245176
Position Surface form Disambiguated ID Type / Status
Subject Dubai Destination E436930 entity
Predicate sire P25213 FINISHED
Object Kingmambo 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: Kingmambo | Statement: [Dubai Destination, sire, Kingmambo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kingmambo
Context triple: [Dubai Destination, sire, Kingmambo]
  • A. Kingmambo chosen
    Kingmambo was a champion Thoroughbred racehorse and highly influential sire known for producing numerous top-class runners worldwide.
  • B. Mtume
    Mtume was an American R&B and jazz-funk musician, songwriter, and producer best known for leading the band Mtume and co-writing the hit song "Juicy Fruit."
  • C. Mambo Kingz
    Mambo Kingz is a Latin music production duo known for crafting reggaeton and urban hits for top artists in the Spanish-speaking music scene.
  • D. Damongo
    Damongo is a town in northern Ghana known as a gateway to Mole National Park and other nearby natural and cultural attractions.
  • E. Mambo
    Mambo was the royal title used for the supreme ruler of the Rozvi Empire in what is now Zimbabwe.
  • 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_69d8b91104e08190a8241f7d260a5162 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4f7e6fbac8190bf252c4337f50c29 completed April 19, 2026, 3:42 p.m.
Created at: April 10, 2026, 10:33 a.m.