Triple

T9578404
Position Surface form Disambiguated ID Type / Status
Subject Why Do Fools Fall in Love E231106 entity
Predicate hasCastMember P2308 FINISHED
Object Lela Rochon E32637 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: Lela Rochon | Statement: [Why Do Fools Fall in Love, hasCastMember, Lela Rochon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lela Rochon
Context triple: [Why Do Fools Fall in Love, hasCastMember, Lela Rochon]
  • A. Lela Rochon chosen
    Lela Rochon is an American actress best known for her breakout role in the 1995 film "Waiting to Exhale" and her work in numerous film and television projects throughout the 1990s.
  • B. Lola Ray Facinelli
    Lola Ray Facinelli is the daughter of American actor Peter Facinelli.
  • C. Alexis Marie Rochon
    Alexis Marie Rochon was an 18th-century French astronomer, physicist, and optician known for his work on achromatic lenses and improvements to optical instruments.
  • D. Marilu Henner
    Marilu Henner is an American actress and author best known for her role as Elaine Nardo on the TV sitcom "Taxi" and for her appearances in numerous film and television projects.
  • E. Retta
    Retta is an American actress and comedian best known for her roles on the television series "Parks and Recreation" and "Good Girls."
  • 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_69ca848091c48190bc313d6620d09555 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd99aece1081908287e03106de020f completed April 1, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69d189ef34c48190974a1a4ca6943a87 completed April 4, 2026, 10 p.m.
Created at: March 30, 2026, 8:05 p.m.