Triple

T22948303
Position Surface form Disambiguated ID Type / Status
Subject Devil in a Blue Dress E569934 entity
Predicate starredActor P5563 FINISHED
Object Mel Winkler 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: Mel Winkler | Statement: [Devil in a Blue Dress, starredActor, Mel Winkler]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mel Winkler
Context triple: [Devil in a Blue Dress, starredActor, Mel Winkler]
  • A. Mel Winkler chosen
    Mel Winkler was an American character actor best known for his distinctive voice work in video games and animation, as well as supporting roles in film and television.
  • B. Michael Winder
    Michael Winder is a screenwriter best known for his work on the 1976 action film "Killer Force."
  • C. Charles Winkler
    Charles Winkler is an American film and television director and producer known for his work on projects such as the boxing drama "Creed."
  • D. Michael Wittenberg
    Michael Wittenberg was an investment adviser best known as the late husband of Broadway star Bernadette Peters.
  • E. Phil Wandscher
    Phil Wandscher is an American guitarist best known as a founding member and lead guitarist of the alt-country band Whiskeytown.
  • 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_69e2459199d08190a8184ee2aa935842 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1819fbf8c8190ad80c93f1507aa73 completed April 29, 2026, 3:57 a.m.
Created at: April 17, 2026, 3:46 p.m.