Triple

T14235218
Position Surface form Disambiguated ID Type / Status
Subject Race to Witch Mountain E352858 entity
Predicate cinematographyBy P1953 FINISHED
Object Greg Gardiner E292629 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: Greg Gardiner | Statement: [Race to Witch Mountain, cinematographyBy, Greg Gardiner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Greg Gardiner
Context triple: [Race to Witch Mountain, cinematographyBy, Greg Gardiner]
  • A. Greg Gardiner chosen
    Greg Gardiner is a film cinematographer best known for his work on the popular Christmas comedy movie "Elf."
  • B. Gerald Hagey
    Gerald Hagey was a Canadian academic and administrator best known as the founding president who led the development of the University of Waterloo into a major institution.
  • C. Gordon Thiessen
    Gordon Thiessen is a Canadian economist who served as Governor of the Bank of Canada in the 1990s and early 2000s.
  • D. Robert Chiarelli
    Robert Chiarelli is a music producer and songwriter known for his work on tracks such as "The Apl Song."
  • E. Gord Brown
    Gord Brown was a Canadian Conservative politician who served as the long-time Member of Parliament for the Ontario riding of Leeds—Grenville.
  • 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_69d8278adc7c8190a9218d69bce3c4e6 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de62411c888190a154acd56fe3fcaf completed April 14, 2026, 3:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd3d0e6abc819097c0c9bdc08387f6 completed May 8, 2026, 1:31 a.m.
Created at: April 10, 2026, 1:07 a.m.