Triple

T14379658
Position Surface form Disambiguated ID Type / Status
Subject Griselda Records E356566 entity
Predicate hasProducer P30366 FINISHED
Object Daringer E1096071 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: Daringer | Statement: [Griselda Records, hasProducer, Daringer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daringer
Context triple: [Griselda Records, hasProducer, Daringer]
  • A. Daringer chosen
    Daringer is an American hip-hop producer best known for crafting the dark, gritty sound associated with the Buffalo-based Griselda collective.
  • B. Daughtrey
    Daughtrey is a surname most notably associated with Martha Craig Daughtrey, an American judge who served on the U.S. Court of Appeals for the Sixth Circuit.
  • C. Darende
    Darende is a historic district and town in eastern Turkey known for its natural scenery, religious sites, and cultural heritage within Malatya Province.
  • D. Darrow
    Darrow is a surname most famously associated with Clarence Darrow, the prominent American lawyer and civil libertarian known for high-profile cases in the early 20th century.
  • E. Bonger
    Bonger is a Dutch surname most notably associated with Johanna van Gogh-Bonger, the key figure in preserving and promoting Vincent van Gogh’s artistic legacy.
  • 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_69d8279163a081908aec45c0e3f1e02f completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de900a67e08190ab1dcf36e6bb3405 completed April 14, 2026, 7:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd551002948190aeb93d245e1449a7 completed May 8, 2026, 3:14 a.m.
Created at: April 10, 2026, 1:16 a.m.