Triple

T7288049
Position Surface form Disambiguated ID Type / Status
Subject Soul Food E163923 entity
Predicate stars P1956 FINISHED
Object Vivica A. Fox E150547 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: Vivica A. Fox | Statement: [Soul Food, stars, Vivica A. Fox]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vivica A. Fox
Context triple: [Soul Food, stars, Vivica A. Fox]
  • A. Vivica A. Fox chosen
    Vivica A. Fox is an American actress and producer known for her roles in films such as Independence Day, Set It Off, and Kill Bill, as well as numerous television series.
  • B. Nicole Ari Parker
    Nicole Ari Parker is an American actress known for her roles in film and television, including prominent performances in romantic comedies and dramas.
  • C. Nia Long
    Nia Long is an American actress known for her roles in films like "Boyz n the Hood," "Love Jones," and "The Best Man," as well as the TV series "The Fresh Prince of Bel-Air."
  • D. Virginia Madsen
    Virginia Madsen is an American actress known for her versatile film and television roles, including acclaimed performances in movies such as "Sideways" and "Candyman."
  • E. Diahnne Abbott
    Diahnne Abbott is an American actress and singer known for her roles in films like "Taxi Driver" and "The King of Comedy."
  • 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_69c6886093b88190a254b1ce6db8bae7 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eb6a73fc8190ae5ce81fd3e46d87 completed March 27, 2026, 8:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7db42c8d48190a548c4242b07fb40 completed March 28, 2026, 1:44 p.m.
Created at: March 27, 2026, 2:59 p.m.