Triple

T10979505
Position Surface form Disambiguated ID Type / Status
Subject Phipps E259462 entity
Predicate hasNotableBearer P458 FINISHED
Object William Phipps E131794 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: William Phipps | Statement: [Phipps, hasNotableBearer, William Phipps]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: William Phipps
Context triple: [Phipps, hasNotableBearer, William Phipps]
  • A. William Phipps chosen
    William Phipps was an American actor best known for providing the speaking voice of Prince Charming in Disney’s animated classic "Cinderella" (1950).
  • B. Samuel Vassall
    Samuel Vassall was a 17th-century English merchant and politician known for resisting King Charles I’s illegal customs duties and later serving as a Member of Parliament.
  • C. William Hutchinson
    William Hutchinson was a 17th-century English merchant and colonial settler in Massachusetts Bay, best known as the husband of religious dissenter Anne Hutchinson.
  • D. Francis Smith
    Francis Smith was a British Army officer best known for leading the regular troops during the opening engagements of the American Revolutionary War at Lexington and Concord in 1775.
  • E. Nathaniel Parker
    Nathaniel Parker is an English actor known for his work in film, television, and theatre, including roles in adaptations of classic literature and popular detective dramas.
  • 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_69d6aa895f4c8190887a15460ef622f4 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d771f7b874819087bf5a858905279b completed April 9, 2026, 9:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69e2d7cb8fe08190b9de7b970968da48 completed April 18, 2026, 1 a.m.
Created at: April 8, 2026, 9:24 p.m.