Triple

T21986325
Position Surface form Disambiguated ID Type / Status
Subject Blood Money E542970 entity
Predicate producer P490 FINISHED
Object DJ Green Lantern 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: DJ Green Lantern | Statement: [Blood Money, producer, DJ Green Lantern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DJ Green Lantern
Context triple: [Blood Money, producer, DJ Green Lantern]
  • A. DJ Green Lantern chosen
    DJ Green Lantern is an American hip hop DJ and producer known for his influential mixtapes, radio shows, and collaborations with major rap artists.
  • B. DJ Alamo
    DJ Alamo is an American hip-hop DJ best known for his work with the influential rap group Brand Nubian during the early 1990s.
  • C. DJ Lethal
    DJ Lethal is a Latvian-American DJ and producer best known as a member of the rap rock band Limp Bizkit and formerly of the hip hop group House of Pain.
  • D. DJ Sincere
    DJ Sincere is a hip-hop DJ best known for his work with the influential New Rochelle rap group Brand Nubian.
  • E. DJ Vance
    DJ Vance is a fictional character from the television series "Hacks," appearing as part of the show's comedic exploration of the entertainment industry.
  • 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_69e0c48136b081908831fa907cc02e18 completed April 16, 2026, 11:14 a.m.
NER Named-entity recognition batch_69f12709cb288190a2620e337fea364c completed April 28, 2026, 9:30 p.m.
Created at: April 16, 2026, 8:04 p.m.