Triple

T14178883
Position Surface form Disambiguated ID Type / Status
Subject Peter Pan’s Flight E351401 entity
Predicate area P175 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: [Peter Pan’s Flight, area, Fantasyland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Fantasyland
Context triple: [Peter Pan’s Flight, area, 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_69d8278834a08190b0f1784e58d7b99c completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de61c90abc8190a9b9dc1f50db59fa completed April 14, 2026, 3:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcf80f03a48190a5374fb6374255a8 completed May 7, 2026, 8:37 p.m.
Created at: April 10, 2026, 1:02 a.m.