Triple

T14807131
Position Surface form Disambiguated ID Type / Status
Subject Bluff City Law E348065 entity
Predicate pilotDirector P16460 FINISHED
Object Michael Dinner E574084 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: Michael Dinner | Statement: [Bluff City Law, pilotDirector, Michael Dinner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Dinner
Context triple: [Bluff City Law, pilotDirector, Michael Dinner]
  • A. Michael Dinner chosen
    Michael Dinner is an American television director, producer, and writer known for his work on numerous acclaimed TV series.
  • B. Michael Boughen
    Michael Boughen is a film producer known for his work on action and thriller movies, including the Jason Statham–starring film "Killer Elite."
  • C. Daniel Dines
    Daniel Dines is a Romanian entrepreneur best known as the co-founder and CEO of UiPath, a leading global robotic process automation (RPA) company.
  • D. Michael Dougherty
    Michael Dougherty is an American filmmaker and screenwriter best known for genre films like Trick 'r Treat and Krampus and for directing the MonsterVerse installment Godzilla: King of the Monsters.
  • E. Michael Wincott
    Michael Wincott is a Canadian character actor known for his distinctive raspy voice and memorable villainous roles in films such as The Crow, Robin Hood: Prince of Thieves, and Nope.
  • 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_69d822ea8b7c819097dfadf3d45545e6 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69decf33b6a08190ab6a4cfeda2cc09c completed April 14, 2026, 11:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe24c8bc6881908736c029943997ae completed May 8, 2026, 6 p.m.
Created at: April 10, 2026, 1:41 a.m.