Triple

T16286131
Position Surface form Disambiguated ID Type / Status
Subject Fair Play E395391 entity
Predicate castMember P1668 FINISHED
Object Patrick Fischler 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: Patrick Fischler | Statement: [Fair Play, castMember, Patrick Fischler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Patrick Fischler
Context triple: [Fair Play, castMember, Patrick Fischler]
  • A. Patrick Fischler chosen
    Patrick Fischler is an American character actor known for his memorable supporting roles in film and television, including appearances in projects like Mulholland Drive, Mad Men, and Lost.
  • B. Jeffrey Wilcke
    Jeffrey Wilcke is a software developer best known as one of the original co-founders of Ethereum and an early core contributor to its implementation.
  • C. Michael Fessier
    Michael Fessier was an American screenwriter and author known for his work on Hollywood films in the 1930s and 1940s, often contributing to romantic comedies and musicals.
  • D. Patrick Friesacher
    Patrick Friesacher is an Austrian racing driver best known for competing in Formula One during the 2005 season.
  • E. Dennis Balthaser
    Dennis Balthaser is a UFO researcher and author best known for his investigations into the Roswell incident and his involvement with the International UFO Museum and Research Center.
  • 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_69d87f22c7248190a54c949738441e2e completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e24914bda08190a5d6315414ee3f76 completed April 17, 2026, 2:52 p.m.
Created at: April 10, 2026, 5:05 a.m.