Triple

T2140074
Position Surface form Disambiguated ID Type / Status
Subject Pete Docter E46739 entity
Predicate directed P7373 FINISHED
Object Up E46400 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: Up | Statement: [Pete Docter, directed, Up]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Up
Context triple: [Pete Docter, directed, Up]
  • A. Up chosen
    Up is a critically acclaimed 2009 Pixar animated film that follows an elderly widower and a young boy on a fantastical balloon-lifted house adventure, noted for its emotional depth and imaginative storytelling.
  • B. UP
    UP is the standard reporting mark used to identify rail equipment owned or operated by the Union Pacific Railroad in North America.
  • C. UP
    UP is a leading South African public research university located in Pretoria, known for its comprehensive range of academic programs and strong research output.
  • D. UP-W
    UP-W is the service designation used by Metra for its Union Pacific West commuter rail line in the Chicago metropolitan area.
  • E. UP 200
    UP 200 is a prominent mid-distance sled dog race held annually in Michigan’s Upper Peninsula, attracting mushers and teams from across North America.
  • 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_69a88a174ab48190a5db20c132e5dccf completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abbe04135c8190ab100b4b3879cb01 completed March 7, 2026, 5:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6533c7f081909860c89a2a53ad49 completed March 9, 2026, 6:14 a.m.
Created at: March 4, 2026, 7:44 p.m.