Triple

T21480999
Position Surface form Disambiguated ID Type / Status
Subject Kimberly J. Brown E529991 entity
Predicate birthName P65 FINISHED
Object Kimberly Jean Brown NE NERFINISHED

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: Kimberly Jean Brown | Statement: [Kimberly J. Brown, birthName, Kimberly Jean Brown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kimberly Jean Brown
Context triple: [Kimberly J. Brown, birthName, Kimberly Jean Brown]
  • A. Kimberly Woodard
    Kimberly Woodard is a television producer best known for her executive production work on the live law-enforcement reality series "Live PD."
  • B. Kimberly J. Brown chosen
    Kimberly J. Brown is an American actress best known for playing Marnie Piper in Disney Channel’s Halloweentown film series.
  • C. Kimberly Denise Jones
    Kimberly Denise Jones is an American rapper, songwriter, and actress best known by her stage name Lil' Kim, a pioneering figure in hardcore hip hop and fashion.
  • D. Teisha Brown
    Teisha Brown is a singer best known as a member of the American R&B group Brownstone.
  • E. Melissa Viviane Jefferson
    Melissa Viviane Jefferson is an American singer, rapper, flutist, and songwriter professionally known as Lizzo, celebrated for her body-positive anthems and energetic performances.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c45acc3881908e38d3f28964152b completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e9ea338f988190a3044f8d02a567fe completed April 23, 2026, 9:45 a.m.
Created at: April 16, 2026, 6:21 p.m.