Triple

T7915028
Position Surface form Disambiguated ID Type / Status
Subject Hamilton Luske E183799 entity
Predicate notableWork P4 FINISHED
Object Fantasia E59661 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: Fantasia | Statement: [Hamilton Luske, notableWork, Fantasia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fantasia
Context triple: [Hamilton Luske, notableWork, Fantasia]
  • A. Fantasia chosen
    Fantasia is a groundbreaking 1940 animated musical film by Walt Disney that combines classical music with innovative animation in a series of imaginative segments.
  • B. Fantasia (album)
    Fantasia is the self-titled second studio album by American Idol winner Fantasia Barrino, showcasing her blend of R&B, soul, and contemporary urban music.
  • C. 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.
  • D. The Wonderful World of Disney
    The Wonderful World of Disney is a long-running American television anthology series that presents Disney-produced films, specials, and family entertainment.
  • E. Fantasyland
    Fantasyland is a themed area in Disney parks that brings classic fairy tales and animated stories to life through rides, attractions, and immersive environments.
  • 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_69ca828efbe48190bd48482650182e79 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3a759b548190af2e2aa0705d7051 completed March 31, 2026, 3:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5be54fdc81909a988114a6f30a13 completed March 31, 2026, 5:30 a.m.
Created at: March 30, 2026, 5:05 p.m.