Triple

T4338432
Position Surface form Disambiguated ID Type / Status
Subject Tyrese Gibson E97519 entity
Predicate notableWork P4 FINISHED
Object Waist Deep E331428 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: Waist Deep | Statement: [Tyrese Gibson, notableWork, Waist Deep]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Waist Deep
Context triple: [Tyrese Gibson, notableWork, Waist Deep]
  • A. Waist Deep chosen
    Waist Deep is a 2006 action-crime drama film about an ex-convict’s desperate attempt to rescue his kidnapped son amid gang violence in Los Angeles.
  • B. 6 Feet Deep
    6 Feet Deep is a pioneering mid-1990s horrorcore hip-hop album by the group Gravediggaz, known for its dark humor, macabre themes, and influential production.
  • C. Ocean Deep
    Ocean Deep is an episode of the documentary series "Planet Earth" that explores the mysterious and extreme environments of the world's deepest oceans and the unique life forms that inhabit them.
  • D. In Too Deep
    In Too Deep is a 1999 crime thriller film about an undercover cop infiltrating a powerful drug syndicate, in which Michael Beach plays a supporting role.
  • E. Wishing Well
    Wishing Well is a popular underground pool feature in Luray Caverns where visitors toss coins while making wishes, with the collected money often donated to charity.
  • 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_69b3454662a481908fbcd0bbfaa3a0a4 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3516dffb48190878f81ffe71a5e82 completed March 12, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5d0af82888190bed294bdec942f4a completed March 14, 2026, 9:18 p.m.
Created at: March 12, 2026, 11:14 p.m.