Triple

T12725483
Position Surface form Disambiguated ID Type / Status
Subject Azonto E304093 entity
Predicate notableSong P4 FINISHED
Object U Go Kill Me E304102 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: U Go Kill Me | Statement: [Azonto, notableSong, U Go Kill Me]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: U Go Kill Me
Context triple: [Azonto, notableSong, U Go Kill Me]
  • A. You Go Kill Me chosen
    "You Go Kill Me" is a popular Azonto-era hip hop/afrobeats track by Ghanaian rapper Sarkodie that helped boost his mainstream success across Africa.
  • B. You Kill Me
    You Kill Me is a 2007 dark comedy crime film about an alcoholic hitman trying to reform his life, directed by John Dahl and starring Ben Kingsley and Téa Leoni.
  • C. Killer Is Me
    "Killer Is Me" is a song by American rock band Alice in Chains, known for its appearance on their 1996 MTV Unplugged performance.
  • D. Kill Me Later
    Kill Me Later is a 2001 darkly comic British-Canadian crime thriller film about a suicidal bank employee caught up in a botched robbery and taken hostage.
  • E. Kill Your Friends
    Kill Your Friends is a darkly comic British film (based on John Niven’s novel) that satirizes the ruthless 1990s music industry through the violent, ambition-fueled rise of an A&R executive.
  • 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_69d7bdf084148190ab9d513dc0735af4 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96415ebe48190ae935bc3a9b00f65 completed April 10, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69f684e61e7081908dec7958e8bc1125 completed May 2, 2026, 11:12 p.m.
Created at: April 9, 2026, 5:25 p.m.