Triple

T15565907
Position Surface form Disambiguated ID Type / Status
Subject Trial & Error E371112 entity
Predicate executiveProducer P7225 FINISHED
Object Matt Miller E1165062 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: Matt Miller | Statement: [Trial & Error, executiveProducer, Matt Miller]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matt Miller
Context triple: [Trial & Error, executiveProducer, Matt Miller]
  • A. Matt Miller chosen
    Matt Miller is a television writer and producer best known for creating the comedy series "Trial & Error."
  • B. Andrew Miller
    Andrew Miller is an American former Major League Baseball relief pitcher known for his dominant left-handed pitching and key postseason performances for multiple teams, including the Cleveland Indians and New York Yankees.
  • C. Matthew Miller
    Matthew Miller is an American television writer and producer best known for developing and executive producing the TV adaptation of the "Lethal Weapon" film franchise.
  • D. Jake Miller
    Jake Miller is an actor known for appearing in the independent drama film "Paranoid Park," directed by Gus Van Sant.
  • E. Dan Miller
    Dan Miller is a central character in the 2007 horror film "The Mist," known as a pragmatic and skeptical local who becomes a key figure in the tense human conflicts that arise when townspeople are trapped in a supermarket by a mysterious, deadly fog.
  • 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_69d85cc6cf40819091f4a5facee1ebe6 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04ddd753c8190b51eaef433258081 completed April 16, 2026, 2:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff56bf8cac81909886de5b82849cb2 completed May 9, 2026, 3:46 p.m.
Created at: April 10, 2026, 4:10 a.m.