Triple

T3328143
Position Surface form Disambiguated ID Type / Status
Subject Josh Brolin E69966 entity
Predicate spouse P13 FINISHED
Object Diane Lane E189720 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: Diane Lane | Statement: [Josh Brolin, spouse, Diane Lane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Diane Lane
Context triple: [Josh Brolin, spouse, Diane Lane]
  • A. Diane Lane chosen
    Diane Lane is an American actress acclaimed for her versatile performances in film and television, with a career spanning from childhood roles to major Hollywood productions.
  • B. Elizabeth Berkley
    Elizabeth Berkley is an American actress best known for her roles in the TV series "Saved by the Bell" and the film "Showgirls."
  • C. Téa Leoni
    Téa Leoni is an American actress and producer best known for her leading roles in film and television, including the political drama series "Madam Secretary."
  • D. Elisabeth Shue
    Elisabeth Shue is an American actress known for her roles in films such as "The Karate Kid," "Adventures in Babysitting," and "Leaving Las Vegas," for which she received an Academy Award nomination.
  • E. Glenne Headly
    Glenne Headly was an American actress known for her versatile film, television, and stage performances, including prominent roles in comedies and dramas from the 1980s onward.
  • 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_69ad85a1829881908942c14075644d0d completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb16f61248190bab10f4ac9e066f7 completed March 8, 2026, 5:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69b367e9e414819088ec4b05495b86e1 completed March 13, 2026, 1:27 a.m.
Created at: March 8, 2026, 3:12 p.m.