Triple

T22448085
Position Surface form Disambiguated ID Type / Status
Subject Four Wives E554915 entity
Predicate cinematography P1953 FINISHED
Object Ernest Haller NE NERFINISHED

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: Ernest Haller | Statement: [Four Wives, cinematography, Ernest Haller]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ernest Haller
Context triple: [Four Wives, cinematography, Ernest Haller]
  • A. Ernest Haller chosen
    Ernest Haller was an American cinematographer best known for his Academy Award-winning work on the classic film "Gone with the Wind."
  • B. Ernest Lavergne
    Ernest Lavergne was a Canadian engineer and entrepreneur best known as the founder of the major engineering and construction firm SNC-Lavalin.
  • C. Louis Eberhardt
    Louis Eberhardt was the founder responsible for establishing the village of Kenmore, New York.
  • D. Jules Eichorn
    Jules Eichorn was an American mountaineer and early Sierra Nevada climbing pioneer known for significant first ascents in California.
  • E. Fernand Etgen
    Fernand Etgen is a Luxembourgish politician who has served as a leading parliamentary figure, including in the role of President of the Chamber of Deputies.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e5113208190ab58c6b595f9d1d0 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15b48be0481909f4601b732424e5b completed April 29, 2026, 1:13 a.m.
Created at: April 16, 2026, 8:48 p.m.