Triple

T22410029
Position Surface form Disambiguated ID Type / Status
Subject Killer Love E553971 entity
Predicate producer P490 FINISHED
Object DJ Frank E 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 Frank E | Statement: [Killer Love, producer, DJ Frank E]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DJ Frank E
Context triple: [Killer Love, producer, DJ Frank E]
  • A. DJ Frank E chosen
    DJ Frank E is an American record producer and songwriter known for crafting pop and hip-hop hits for major artists across the 2000s and 2010s.
  • B. Doug E. Fresh
    Doug E. Fresh is an American rapper, record producer, and pioneering human beatbox artist widely regarded as one of the originators of beatboxing in hip-hop.
  • C. Lord Finesse
    Lord Finesse is an American hip-hop MC and producer from the Bronx, best known as a founding member of the Diggin' in the Crates Crew and for his influential work in 1990s East Coast rap.
  • D. DJ Hi-Tek
    DJ Hi-Tek is a hip-hop producer and DJ best known for his work with Mos Def and Talib Kweli, particularly as part of the group Reflection Eternal.
  • E. DJ Akademiks
    DJ Akademiks is a Jamaican-American media personality and hip-hop commentator known for his YouTube coverage of rap news, online beefs, and cultural controversies.
  • 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_69e11e4e6ce8819085a1e06d886bf21c completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f158bb9ef88190a773d82ac9ed7a55 completed April 29, 2026, 1:02 a.m.
Created at: April 16, 2026, 8:46 p.m.