Triple

T9917841
Position Surface form Disambiguated ID Type / Status
Subject Tokyo Disneyland E185914 entity
Predicate hasThemedLand P13439 FINISHED
Object Fantasyland E185274 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: Fantasyland | Statement: [Tokyo Disneyland, hasThemedLand, Fantasyland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fantasyland
Context triple: [Tokyo Disneyland, hasThemedLand, Fantasyland]
  • A. Fantasyland chosen
    Fantasyland is a themed area in Disney parks that brings classic fairy tales and animated stories to life through rides, attractions, and immersive environments.
  • B. 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.
  • C. Lands of Disneyland
    Lands of Disneyland are themed areas within the Disneyland park, each designed with distinct settings, attractions, and experiences that immerse guests in different stories and worlds.
  • D. Zauberland
    Zauberland is a poetic nickname for the North Sea island of Juist, highlighting its idyllic, almost magical natural atmosphere.
  • E. Adventureland
    Adventureland is a themed land found in several Disney parks, designed to evoke exotic, tropical locales through attractions, lush landscaping, and immersive storytelling.
  • 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_69ca829b45f481909040f7b99a1976ed completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cdb5673f108190914e0c172dddc65f completed April 2, 2026, 12:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69d20dec42848190ab9f8663155df83f completed April 5, 2026, 7:23 a.m.
Created at: March 30, 2026, 8:42 p.m.