Triple

T9917842
Position Surface form Disambiguated ID Type / Status
Subject Tokyo Disneyland E185914 entity
Predicate hasThemedLand P13439 FINISHED
Object Toontown E173784 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: Toontown | Statement: [Tokyo Disneyland, hasThemedLand, Toontown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toontown
Context triple: [Tokyo Disneyland, hasThemedLand, Toontown]
  • A. Toontown
    Toontown is the vibrant, cartoon-filled fictional city where animated characters live and interact with humans in the film "Who Framed Roger Rabbit."
  • B. Mickey's Toontown chosen
    Mickey's Toontown is a whimsical, cartoon-themed land in Disney parks where guests can explore the colorful homes and neighborhoods of Mickey Mouse and his friends.
  • C. Mickey's Toontown Depot
    Mickey's Toontown Depot is a themed railroad station in Disneyland Park that serves as the stop for the Disneyland Railroad in the Mickey's Toontown area.
  • D. Discoveryland
    Discoveryland is a retro-futuristic themed land at Disneyland Paris inspired by the visionary works of Jules Verne and classic science fiction.
  • E. Storybook Land
    Storybook Land is a fairy tale–themed amusement park in Aberdeen, South Dakota, featuring storybook characters, themed rides, and attractions for young children and families.
  • 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.