Triple

T8037359
Position Surface form Disambiguated ID Type / Status
Subject Leonard Franklin Slye E187139 entity
Predicate hasPet P8711 FINISHED
Object Trigger E57934 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: [Leonard Franklin Slye, hasPet, Trigger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Trigger
Context triple: [Leonard Franklin Slye, hasPet, Trigger]
  • A. Trigger chosen
    Trigger was the famous golden palomino horse best known as Roy Rogers’ iconic movie and television mount in mid-20th-century Westerns.
  • B. Trigger
    Trigger is a Canadian drama film featuring Molly Parker in a leading role.
  • C. 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.
  • D. Trace
    Trace is a large-scale installation by Chinese artist Ai Weiwei composed of thousands of LEGO portraits depicting political prisoners and activists from around the world.
  • E. Trieb
    Trieb is a district or locality within the town of Lichtenfels in the Upper Franconia region of Bavaria, Germany.
  • 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_69ca82ae2d1081909dbfee42b41db419 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3f188e1c8190b92760c91d31f2df completed March 31, 2026, 3:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69cc56fa97ac8190a0bd646d9ec345e4 completed March 31, 2026, 11:21 p.m.
Created at: March 30, 2026, 5:23 p.m.