Triple

T8841339
Position Surface form Disambiguated ID Type / Status
Subject Pitbull E210396 entity
Predicate stageName P7872 FINISHED
Object Pitbull E210396 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: Pitbull | Statement: [Pitbull, stageName, Pitbull]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pitbull
Context triple: [Pitbull, stageName, Pitbull]
  • A. Pitbull chosen
    Pitbull is an American rapper, singer, and songwriter known for his high-energy party anthems and numerous international pop and Latin music collaborations.
  • B. Yandel
    Yandel is a Puerto Rican reggaeton singer and songwriter best known as one half of the duo Wisin & Yandel and for his influential solo work in Latin urban music.
  • C. Xzibit
    Xzibit is an American rapper, actor, and television host best known for fronting the MTV car-customization show "Pimp My Ride."
  • D. Booba
    Booba is a prominent French rapper and entrepreneur known for his influential role in the French hip-hop scene and numerous hit albums and collaborations.
  • E. Bow Wow
    Bow Wow is an American rapper and actor who rose to fame as a child star in the early 2000s with hit singles and roles in films like "Like Mike."
  • 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_69ca838967bc8190b46c3c80a2887ea4 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc60876c6c8190b1b490e447e1cf4b completed April 1, 2026, 12:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69cf899c5b288190b854acebc9fe33d1 completed April 3, 2026, 9:34 a.m.
Created at: March 30, 2026, 6:48 p.m.