Triple

T14517089
Position Surface form Disambiguated ID Type / Status
Subject Hollywood’s Bleeding E340547 entity
Predicate producer P490 FINISHED
Object DJ Dahi E135452 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 Dahi | Statement: [Hollywood’s Bleeding, producer, DJ Dahi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DJ Dahi
Context triple: [Hollywood’s Bleeding, producer, DJ Dahi]
  • A. DJ Dahi chosen
    DJ Dahi is an American record producer and DJ known for his innovative, genre-blending work with major hip-hop and R&B artists.
  • B. DJ Shok
    DJ Shok is a hip-hop producer best known for his work with DMX, including producing the acclaimed track "Slippin'."
  • C. 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.
  • D. DJ Die
    DJ Die is a British drum and bass DJ and producer from Bristol, known for his influential role in shaping the city’s distinctive sound and its global reputation in electronic music.
  • E. DJ Mekalek
    DJ Mekalek is a hip-hop DJ and producer known for his intricate turntablism, underground collaborations, and work with groups like Time Machine.
  • 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_69d822d9c0408190b9a2b3643e58bb4d completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69de9a6f50208190b687b505f5cd1aa2 completed April 14, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6da80dc88190afa96760efb0c7de completed May 8, 2026, 4:59 a.m.
Created at: April 10, 2026, 1:21 a.m.