Triple

T18474103
Position Surface form Disambiguated ID Type / Status
Subject Paul Satterfield E451382 entity
Predicate notableWork P4 FINISHED
Object Bambi NE NERFINISHED

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: Bambi | Statement: [Paul Satterfield, notableWork, Bambi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bambi
Context triple: [Paul Satterfield, notableWork, Bambi]
  • A. Bambi chosen
    Bambi is a classic 1942 animated film produced by Walt Disney that follows the life and coming-of-age of a young deer in the forest.
  • B. Bambi
    Bambi is the Hall of Fame American football wide receiver Lance Alworth, renowned for his speed, agility, and acrobatic pass-catching.
  • C. Bambi II
    Bambi II is a 2006 direct-to-video animated film from Disney that explores Bambi’s childhood and relationship with his father, the Great Prince of the Forest.
  • D. Lady and the Tramp
    Lady and the Tramp is a classic 1955 American animated romantic film produced by Disney, renowned for its love story between two dogs from different social backgrounds and its iconic spaghetti dinner scene.
  • E. Dumbo
    Dumbo is the nickname of the Curtiss C-46 Commando, a World War II-era American military transport aircraft known for its large cargo capacity and service in challenging flying conditions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8d38465a0819099b9b42d2a662ac1 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e53062387481909d4503fc963f9913 completed April 19, 2026, 7:43 p.m.
Created at: April 10, 2026, 11:34 a.m.