Triple

T15417422
Position Surface form Disambiguated ID Type / Status
Subject DJ Green Lantern E369278 entity
Predicate name P16 FINISHED
Object DJ Green Lantern E369278 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: DJ Green Lantern | Statement: [DJ Green Lantern, name, DJ Green Lantern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DJ Green Lantern
Context triple: [DJ Green Lantern, name, 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 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.
  • C. 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.
  • D. DJ Kaywise
    DJ Kaywise is a popular Nigerian disc jockey and music producer known for his hit street anthems, mixtapes, and collaborations with top Afrobeats artists.
  • E. DJ Lord
    DJ Lord is an American turntablist and hip hop DJ best known as the longtime touring and performance DJ for the influential rap group Public Enemy.
  • 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_69d85a1849f48190bf898068b2806fae completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ea8a8a081909749db1b29d85fcc completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff1a78f9cc819097a6ff1e0cbdbcf3 completed May 9, 2026, 11:28 a.m.
Created at: April 10, 2026, 3:20 a.m.