Triple

T13254713
Position Surface form Disambiguated ID Type / Status
Subject Young Carl Fredricksen E315629 entity
Predicate versionOf P31922 FINISHED
Object Carl Fredricksen E236525 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: Carl Fredricksen | Statement: [Young Carl Fredricksen, versionOf, Carl Fredricksen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carl Fredricksen
Context triple: [Young Carl Fredricksen, versionOf, Carl Fredricksen]
  • A. Carl Fredricksen chosen
    Carl Fredricksen is the elderly, widowed former balloon salesman who embarks on an adventurous journey to South America in Pixar's animated film "Up."
  • B. George Land
    George Land is the largest island in the remote Arctic archipelago of Franz Josef Land in northern Russia.
  • C. Woodie
    Woodie is a central character known for embodying the laid-back, carefree spirit associated with "good vibes."
  • D. Elwood P. Dowd
    Elwood P. Dowd is the amiable, eccentric protagonist of the play and film "Harvey," known for his unwavering friendship with an invisible six-foot-tall rabbit.
  • E. Irwin Keyes
    Irwin Keyes was an American character actor best known for his imposing physique and roles in films and TV shows such as "The Jeffersons" and various horror and comedy movies.
  • 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_69d806b1072881909e46bd212259c5f0 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98f7517048190b4eac4e44e81ff66 completed April 11, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716c90c5c8190a6de94b92db12210 completed May 3, 2026, 9:35 a.m.
Created at: April 9, 2026, 9:24 p.m.