Triple

T7643487
Position Surface form Disambiguated ID Type / Status
Subject Brenda Chapman E173064 entity
Predicate spouse P13 FINISHED
Object Kevin Lima E339899 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: Kevin Lima | Statement: [Brenda Chapman, spouse, Kevin Lima]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kevin Lima
Context triple: [Brenda Chapman, spouse, Kevin Lima]
  • A. Kevin Lima chosen
    Kevin Lima is an American film director, animator, and screenwriter best known for his work on Disney animated features such as "A Goofy Movie," "Tarzan," and the live-action/animated film "Enchanted."
  • B. Tony Almeida
    Tony Almeida is a key fictional Counter Terrorist Unit agent in the television series "24," known for his complex loyalties and evolving role across multiple seasons.
  • C. Daniel Lugo
    Daniel Lugo is the ambitious, bodybuilding ringleader of the criminal scheme at the center of the dark comedy crime film "Pain & Gain."
  • D. Mark Vicente
    Mark Vicente is a cinematographer and filmmaker best known for his work on the documentary "What the Bleep Do We Know!?" and his involvement in the NXIVM organization.
  • E. Carlos Lemos
    Carlos Lemos was a Brazilian architect known for his work on prominent modernist projects such as São Paulo’s iconic Copan Building.
  • 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_69c6995360188190968ee57b72a1627f completed March 27, 2026, 2:50 p.m.
NER Named-entity recognition batch_69c6faef96908190a7724b204f9d8c9e completed March 27, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69c870d510f08190ad7706f582e8c1a0 completed March 29, 2026, 12:22 a.m.
Created at: March 27, 2026, 3:58 p.m.