Triple

T12030132
Position Surface form Disambiguated ID Type / Status
Subject My Rifle, My Pony and Me E286381 entity
Predicate sungByCharacter P14884 FINISHED
Object Colorado Ryan E286378 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: Colorado Ryan | Statement: [My Rifle, My Pony and Me, sungByCharacter, Colorado Ryan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Colorado Ryan
Context triple: [My Rifle, My Pony and Me, sungByCharacter, Colorado Ryan]
  • A. Colorado Ryan chosen
    Colorado Ryan is a young, skilled gunslinger and ally of Sheriff John T. Chance in the classic 1959 Western film "Rio Bravo."
  • B. Brad Oscar
    Brad Oscar is an American stage actor and singer best known for his comedic roles in major Broadway musicals, including his acclaimed work in Mel Brooks’s The Producers.
  • C. Arizona Robbins
    Arizona Robbins is a fictional pediatric surgeon on the television series Grey’s Anatomy, known for her upbeat personality, strong surgical skills, and impactful LGBTQ+ storyline.
  • D. Ryan Gravel
    Ryan Gravel is an urban planner and designer best known for conceiving the Atlanta BeltLine, a transformative redevelopment and transit project encircling Atlanta.
  • E. Chris Loken
    Chris Loken is the mother of American actress and model Kristanna Loken.
  • 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_69d6ab4669e48190b59246358b0383ab completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903f24490819092ec911d6ed8e24b completed April 10, 2026, 2:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60a613054819082f7900a6ba8fbf8 completed May 2, 2026, 2:29 p.m.
Created at: April 8, 2026, 9:47 p.m.