Triple

T13670742
Position Surface form Disambiguated ID Type / Status
Subject Richard Johnson E327740 entity
Predicate spouse P13 FINISHED
Object Kim Novak E414298 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: Kim Novak | Statement: [Richard Johnson, spouse, Kim Novak]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kim Novak
Context triple: [Richard Johnson, spouse, Kim Novak]
  • A. Kim Novak chosen
    Kim Novak is an American actress best known for her roles in classic 1950s and 1960s films, particularly Alfred Hitchcock’s "Vertigo."
  • B. Lesley Caron
    Lesley Caron is a British theatre director known for her work on stage productions and for being married to fellow director Peter Hall.
  • C. Ava Gardner
    Ava Gardner was a celebrated American film actress and Hollywood icon of the 1940s and 1950s, renowned for her beauty, charisma, and roles in classics such as "The Killers" and "Mogambo."
  • D. Lauren Bacall
    Lauren Bacall was an iconic American film and stage actress known for her sultry voice, striking looks, and classic roles in 1940s Hollywood noir films.
  • E. Jean Kerr
    Jean Kerr was an American author and playwright best known for her humorous essays and plays about suburban family life, including the bestseller "Please Don’t Eat the Daisies."
  • 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_69d8076f1fa8819094664a59b55010df completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc6599c248190b7f134b5b9947a23 completed April 12, 2026, 4:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe967cea3c81909d9b600501897a41 completed May 9, 2026, 2:05 a.m.
Created at: April 9, 2026, 9:53 p.m.