Triple

T14348076
Position Surface form Disambiguated ID Type / Status
Subject Cuba Gooding Jr. E355779 entity
Predicate spouse P13 FINISHED
Object Sara Kapfer E355779 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: Sara Kapfer | Statement: [Cuba Gooding Jr., spouse, Sara Kapfer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sara Kapfer
Context triple: [Cuba Gooding Jr., spouse, Sara Kapfer]
  • A. Sara Kapfer chosen
    Sara Kapfer is an American schoolteacher best known as the longtime wife of actor Cuba Gooding Jr.
  • B. Catherine Hapka
    Catherine Hapka is an American author known for writing and co-writing numerous children's and young adult books, including equestrian-themed novels.
  • C. Sara Braun
    Sara Braun was a prominent late 19th- and early 20th-century businesswoman and philanthropist in Chilean Patagonia, known for her influential role in regional development and society.
  • D. Sara Ruppenthal
    Sara Ruppenthal was the first wife of Grateful Dead guitarist Jerry Garcia, whom he married in the early 1960s before the band rose to fame.
  • E. Sara Haardt
    Sara Haardt was an American writer and English professor known for her short stories and essays, as well as for her marriage to journalist and critic H. L. Mencken.
  • 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_69d82790a7e08190877e2d349b2e8d8e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8e8d081c8190ac805726a3e98f4c completed April 14, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd46a12ad08190a2f0dc5890ed5ce9 completed May 8, 2026, 2:12 a.m.
Created at: April 10, 2026, 1:14 a.m.