Triple

T2632287
Position Surface form Disambiguated ID Type / Status
Subject Fantasia E59661 entity
Predicate director P255 FINISHED
Object Norman Ferguson E70797 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: Norman Ferguson | Statement: [Fantasia, director, Norman Ferguson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norman Ferguson
Context triple: [Fantasia, director, Norman Ferguson]
  • A. Norman Ferguson chosen
    Norman Ferguson was an American animator and film director at Walt Disney Studios, best known for his influential work on classic Disney features during the Golden Age of animation.
  • B. Norman Winslow
    Norman Winslow is an architect best known for his role in designing Portland, Oregon’s iconic public space, Pioneer Courthouse Square.
  • C. Norman Riley
    Norman Riley is a distinguished mathematician and fluid dynamicist recognized for his influential contributions to theoretical and applied fluid mechanics.
  • D. Norman Rosemont
    Norman Rosemont was an American television and film producer best known for his high-quality adaptations of classic literary works.
  • E. Frank Armstrong Crawford
    Frank Armstrong Crawford was a 19th-century American philanthropist best known as the second wife of railroad magnate Cornelius Vanderbilt and a major benefactor of Vanderbilt University.
  • 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_69ab4ac8596c8190b34997e73d9e991c completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd8c6e540819087c7f92432b27b0f completed March 7, 2026, 7:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69b12df6ad908190b0b484b6fd82ffb5 completed March 11, 2026, 8:55 a.m.
Created at: March 6, 2026, 9:50 p.m.