Triple

T6598746
Position Surface form Disambiguated ID Type / Status
Subject How the West Was Won E148541 entity
Predicate editingBy P1954 FINISHED
Object Harold F. Kress E155211 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: Harold F. Kress | Statement: [How the West Was Won, editingBy, Harold F. Kress]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Harold F. Kress
Context triple: [How the West Was Won, editingBy, Harold F. Kress]
  • A. Harold F. Kress chosen
    Harold F. Kress was an American film editor renowned for his work on numerous classic Hollywood films and for winning multiple Academy Awards for Best Film Editing.
  • B. Harold M. Shaw
    Harold M. Shaw was an early American film director and actor known for his pioneering work in silent cinema during the 1910s.
  • C. Harold C. Mayer
    Harold C. Mayer was an American financier best known as one of the co-founders of the investment bank Bear Stearns.
  • D. Frank Seiberling
    Frank Seiberling was an American industrialist best known for founding the Goodyear Tire & Rubber Company, which became one of the world’s leading tire manufacturers.
  • E. Edward M. Kern
    Edward M. Kern was a 19th-century American topographer and explorer after whom California’s Kern County was named.
  • 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_69c687e7b8688190811ffee72e096468 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6aeeffdf0819090af7bba918bef84 completed March 27, 2026, 4:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6e43224dc81909dea493a5ee2726e completed March 27, 2026, 8:10 p.m.
Created at: March 27, 2026, 1:56 p.m.