Triple

T13982366
Position Surface form Disambiguated ID Type / Status
Subject Fantastic Four: Rise of the Silver Surfer E336343 entity
Predicate screenwriter P2831 FINISHED
Object Don Payne E213974 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: Don Payne | Statement: [Fantastic Four: Rise of the Silver Surfer, screenwriter, Don Payne]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Don Payne
Context triple: [Fantastic Four: Rise of the Silver Surfer, screenwriter, Don Payne]
  • A. Don Payne chosen
    Don Payne was an American screenwriter and producer best known for his work on comedic television series like "The Simpsons" and superhero films such as "Thor."
  • B. Bill Graves
    Bill Graves is an American politician who served as the 43rd Governor of Kansas from 1995 to 2003.
  • C. Howard A. Smith
    Howard A. Smith was a film editor best known for his work on classic Hollywood movies, including the 1961 romantic comedy "Breakfast at Tiffany's."
  • D. Don Roberts
    Don Roberts is a software engineer and author known for his contributions to object-oriented design and refactoring, including work on the influential book "Refactoring: Improving the Design of Existing Code."
  • E. Howard E. Smith
    Howard E. Smith is a film editor best known for his work on major Hollywood productions, including the shark thriller "Deep Blue Sea."
  • 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_69d81c639e808190a0e4b4f3d31c6a59 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2ea2e8808190a1203a6386224bd8 completed April 14, 2026, 12:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd192d09e481909ba3b7522cf661a6 completed May 7, 2026, 10:58 p.m.
Created at: April 9, 2026, 10:18 p.m.