Triple

T17476279
Position Surface form Disambiguated ID Type / Status
Subject Walter Tibbets E425545 entity
Predicate name P16 FINISHED
Object Walter Tibbets 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: Walter Tibbets | Statement: [Walter Tibbets, name, Walter Tibbets]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Walter Tibbets
Context triple: [Walter Tibbets, name, Walter Tibbets]
  • A. Walter Tibbets chosen
    Walter Tibbets is an individual notable enough to be specifically cited as a bearer of the surname Tibbets.
  • B. John C. Tibbets
    John C. Tibbets is an American film historian, author, and former television broadcaster known for his work on cinema history and interviews with prominent filmmakers and actors.
  • C. Luther Tibbets
    Luther Tibbets was a 19th-century American horticulturist and citrus grower, best known for helping introduce and popularize the navel orange in California.
  • D. Andrew Tibbets
    Andrew Tibbets is an individual notable enough to be specifically cited as a bearer of the surname Tibbets.
  • E. Clyde Pangborn
    Clyde Pangborn was an American aviator best known for completing the first nonstop trans-Pacific flight from Japan to the United States in 1931.
  • 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_69d889dbc2e88190b18ea6115e819258 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e451bc3f908190b2c7a2d1f75a43f2 completed April 19, 2026, 3:53 a.m.
Created at: April 10, 2026, 5:47 a.m.