Triple

T15689481
Position Surface form Disambiguated ID Type / Status
Subject Peppy Miller E380287 entity
Predicate helpsCharacter P7748 FINISHED
Object George Valentin E380286 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: George Valentin | Statement: [Peppy Miller, helpsCharacter, George Valentin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: George Valentin
Context triple: [Peppy Miller, helpsCharacter, George Valentin]
  • A. George Valentin chosen
    George Valentin is the charismatic silent film star whose career and personal life are upended by the rise of talking pictures in the film "The Artist."
  • B. Luc Durand
    Luc Durand is a Canadian architect best known for designing the iconic Habitat 67 housing complex in Montreal.
  • C. Rex Grignon
    Rex Grignon is an acclaimed animation director and supervisor best known for his character animation work on major DreamWorks films such as the Shrek series and Madagascar.
  • D. Jean Rochon
    Jean Rochon was a Canadian physician and politician best known for serving as Quebec’s Minister of Health and Social Services and for leading major health system reforms in the province.
  • E. Jim Hugunin
    Jim Hugunin is a software developer best known for creating the IronPython implementation of Python for the .NET framework and contributing to dynamic language integration on Microsoft platforms.
  • 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_69d86d99e860819094b6957cde470f2c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f4e59988190aaf12f6a07c8f0e4 completed April 16, 2026, 2:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff756ffcc88190a72440c7b40711ff completed May 9, 2026, 5:57 p.m.
Created at: April 10, 2026, 4:44 a.m.