Triple

T11320099
Position Surface form Disambiguated ID Type / Status
Subject Don McKellar E268069 entity
Predicate notableWork P4 FINISHED
Object Trigger E574652 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: Trigger | Statement: [Don McKellar, notableWork, Trigger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Trigger
Context triple: [Don McKellar, notableWork, Trigger]
  • A. Trigger
    Trigger was the famous golden palomino horse best known as Roy Rogers’ iconic movie and television mount in mid-20th-century Westerns.
  • B. Trigger chosen
    Trigger is a Canadian drama film featuring Molly Parker in a leading role.
  • C. Trigger
    Trigger is a dim-witted yet lovable road sweeper from the British sitcom "Only Fools and Horses," known for his deadpan delivery and iconic broom joke.
  • D. Trigger Happy
    Trigger Happy is a manic, gun-slinging gremlin Skylander known for his wild personality and rapid-fire golden pistols in the Skylanders video game series.
  • E. The Trigger
    The Trigger is a science fiction novel by Michael P. Kube-McDowell (from a story by Arthur C. Clarke) that explores the social and political consequences of a technology capable of detonating or neutralizing explosives at a distance.
  • 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_69d6aaca5c24819083db46a30d86cb34 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9de875481908acfa56015d4b46f completed April 9, 2026, 6:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69e525e2549081909ec99e4c7006fd66 completed April 19, 2026, 6:58 p.m.
Created at: April 8, 2026, 9:32 p.m.