Triple

T8766443
Position Surface form Disambiguated ID Type / Status
Subject Thank You for Smoking E208349 entity
Predicate character P662 FINISHED
Object Nick Naylor E757296 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: Nick Naylor | Statement: [Thank You for Smoking, character, Nick Naylor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nick Naylor
Context triple: [Thank You for Smoking, character, Nick Naylor]
  • A. Nick Naylor chosen
    Nick Naylor is a charismatic, smooth-talking tobacco lobbyist known for his witty, amoral spin-doctoring in the satirical world of public relations.
  • B. Mike Norton
    Mike Norton is the central character in the modern Western film "The Three Burials of Melquiades Estrada," whose actions and moral journey drive the story’s exploration of guilt, justice, and redemption.
  • C. Nick Reynolds
    Nick Reynolds was an American folk musician best known as a founding member and vocalist of the influential folk group The Kingston Trio.
  • D. Edward Pawley
    Edward Pawley was an American actor known for his work in 1930s and 1940s films and radio dramas.
  • E. Dan Sullivan
    Dan Sullivan is a Republican U.S. Senator from Alaska, known for his work on national security, energy policy, and Arctic issues.
  • 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_69ca835df7e08190ac875664cca8f9ca completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5ee97fd0819087ef8fe14b37ae43 completed March 31, 2026, 11:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf6f1bf97c8190a158a38bd2babb83 completed April 3, 2026, 7:41 a.m.
Created at: March 30, 2026, 6:41 p.m.