Triple

T2088777
Position Surface form Disambiguated ID Type / Status
Subject Gordon and Betty Moore Foundation E32617 entity
Predicate foundedBy P104 FINISHED
Object Betty Moore E141762 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: Betty Moore | Statement: [Gordon and Betty Moore Foundation, foundedBy, Betty Moore]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Betty Moore
Context triple: [Gordon and Betty Moore Foundation, foundedBy, Betty Moore]
  • A. Betty Furness
    Betty Furness was an American actress and television personality best known for her film roles in the 1930s and later as a pioneering consumer affairs advocate on TV.
  • B. Shirley Smith
    Shirley Smith is an artist best known for designing the original first-edition cover of Harper Lee’s novel "To Kill a Mockingbird."
  • C. Betty Irene Whitaker chosen
    Betty Irene Whitaker is the wife of Intel co-founder and philanthropist Gordon E. Moore and a partner in his philanthropic endeavors.
  • D. Betty Jaynes
    Betty Jaynes was an American soprano and film actress best known for her musical roles in late 1930s MGM productions.
  • E. Betty Bronson
    Betty Bronson was an American film actress best known for her roles in silent and early sound films, including her iconic portrayal of Peter Pan in the 1924 adaptation.
  • 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_69a885eba0708190999696a45cbec816 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abba712388819091d68a4bb99f6b17 completed March 7, 2026, 5:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69b0559265388190b070de8b92c6e95b completed March 10, 2026, 5:32 p.m.
Created at: March 4, 2026, 7:43 p.m.