Triple

T12031485
Position Surface form Disambiguated ID Type / Status
Subject Tyler Perry E286419 entity
Predicate givenName P17 FINISHED
Object Emmitt E961387 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: Emmitt | Statement: [Tyler Perry, givenName, Emmitt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emmitt
Context triple: [Tyler Perry, givenName, Emmitt]
  • A. Emmitt
    Emmitt is a masculine given name most famously associated with Pro Football Hall of Fame running back Emmitt Smith.
  • B. Payton
    Payton is the surname of Sean Payton, a prominent American football coach best known for his long tenure with the New Orleans Saints.
  • C. Terrell
    Terrell is a small city in Kaufman County, Texas, known as an outlying suburb of the Dallas–Fort Worth metropolitan area.
  • D. Terrell
    Terrell is a masculine given name most notably associated with American athletes, particularly in professional football and basketball.
  • E. Emmitt Perry Jr. chosen
    Emmitt Perry Jr., better known as Tyler Perry, is an American filmmaker, playwright, and actor renowned for creating and portraying the character Madea and building a media empire centered on African-American audiences.
  • 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_69d6ab4669e48190b59246358b0383ab completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903f24490819092ec911d6ed8e24b completed April 10, 2026, 2:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f646423c819088575a7032e6a9a3 completed May 2, 2026, 1:04 p.m.
Created at: April 8, 2026, 9:47 p.m.