Triple

T16291477
Position Surface form Disambiguated ID Type / Status
Subject Darnell Williams E395532 entity
Predicate givenName P17 FINISHED
Object Darnell E859430 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: Darnell | Statement: [Darnell Williams, givenName, Darnell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Darnell
Context triple: [Darnell Williams, givenName, Darnell]
  • A. Darnell chosen
    Darnell is a surname of English origin borne by various notable individuals, including the American actress Linda Darnell.
  • B. Darell
    Darell is a surname most notably associated with characters in Isaac Asimov’s Foundation series, including the psychohistorian Bayta Darell.
  • C. Darell
    Darell is a Puerto Rican reggaeton and Latin trap singer and rapper known for his collaborations on major urban Latin hits.
  • D. Darnell Lewis
    Darnell Lewis is a central comedic character in the film "Get Hard," portrayed as a small-business owner who helps a wealthy, naive financier prepare for prison life.
  • E. Denzell
    Denzell is a given name that serves as an alternative spelling of the more common name Denzel.
  • 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_69d87f22c7248190a54c949738441e2e completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e24919345881909ba4e7fe2e59340f completed April 17, 2026, 2:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a001f97895081909f22ded3507afe14 completed May 10, 2026, 6:03 a.m.
Created at: April 10, 2026, 5:05 a.m.