Triple

T4035361
Position Surface form Disambiguated ID Type / Status
Subject Fish in the Dark E83814 entity
Predicate lightingDesigner P25110 FINISHED
Object Brian MacDevitt E327203 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: Brian MacDevitt | Statement: [Fish in the Dark, lightingDesigner, Brian MacDevitt]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brian MacDevitt
Context triple: [Fish in the Dark, lightingDesigner, Brian MacDevitt]
  • A. Brian MacDevitt chosen
    Brian MacDevitt is a Tony Award–winning American lighting designer renowned for his work on numerous high-profile Broadway productions.
  • B. Paul Darrow
    Paul Darrow was the son of famed American lawyer Clarence Darrow and a businessman who managed many of his father's financial affairs.
  • C. Gareth Roberts
    Gareth Roberts is a British television writer and novelist best known for his work on the revived Doctor Who series and related media.
  • D. Nicholas Hooper
    Nicholas Hooper is a British film and television composer best known for scoring the Harry Potter films "Order of the Phoenix" and "Half-Blood Prince."
  • E. Chris McKenna
    Chris McKenna is an American screenwriter and producer known for his work on films like the Marvel Cinematic Universe’s Spider-Man series and TV shows such as Community.
  • 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_69aed92f7cf0819098e0539bdcc3767f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefb132f6c8190937acd35a6a5a9e4 completed March 9, 2026, 4:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5629748d88190984cce08eef05e9c completed March 14, 2026, 1:28 p.m.
Created at: March 9, 2026, 3:36 p.m.