Triple

T13274103
Position Surface form Disambiguated ID Type / Status
Subject The Safecracker E316141 entity
Predicate screenwriter P2831 FINISHED
Object John Paxton E229591 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: John Paxton | Statement: [The Safecracker, screenwriter, John Paxton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: John Paxton
Context triple: [The Safecracker, screenwriter, John Paxton]
  • A. John Paxton chosen
    John Paxton was an American screenwriter known for his acclaimed adaptations of literary works and his contributions to mid-20th-century Hollywood cinema.
  • B. Steuart Pittman
    Steuart Pittman is a Maryland politician who serves as the county executive of Anne Arundel County, focusing on issues such as responsible development, environmental protection, and public services.
  • C. Paul Bransom
    Paul Bransom was an American illustrator and wildlife artist best known for his detailed animal drawings in early 20th-century books and magazines.
  • D. Roger Bresnahan
    Roger Bresnahan was an innovative early 20th-century Major League Baseball catcher and Hall of Famer, known for pioneering the use of protective equipment such as shin guards.
  • E. Lee Gilmer
    Lee Gilmer was an individual significant enough to local aviation or the surrounding community that a regional airport was named in his honor.
  • 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_69d806b1d9ac8190852c5571d5bd5f0f completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9904193bc8190af4155750bcf32f6 completed April 11, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69f70a51d458819080b8c8f3a4df0f52 completed May 3, 2026, 8:41 a.m.
Created at: April 9, 2026, 9:26 p.m.