Triple

T7892530
Position Surface form Disambiguated ID Type / Status
Subject Tokyo Disneyland Hotel E183269 entity
Predicate city P40 FINISHED
Object Urayasu E937077 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: Urayasu | Statement: [Tokyo Disneyland Hotel, city, Urayasu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Urayasu
Context triple: [Tokyo Disneyland Hotel, city, Urayasu]
  • A. Urayasu chosen
    Urayasu is a city in Chiba Prefecture, Japan, best known as the home of Tokyo Disney Resort and its associated entertainment and shopping complexes.
  • B. Akishima
    Akishima is a city in western Tokyo, Japan, known as part of the Tama area and characterized by its residential neighborhoods and light industry.
  • C. Tokorozawa
    Tokorozawa is a commuter city in the Greater Tokyo area of Japan, known for its residential neighborhoods, aviation history, and role as a transport hub in southern Saitama.
  • D. Utsunomiya
    Utsunomiya is a city in Tochigi Prefecture, Japan, known as a regional commercial center and for its specialty gyoza (dumplings).
  • E. Yokkaichi
    Yokkaichi is an industrial port city in central Japan known for its petrochemical complexes and role as a major manufacturing hub.
  • 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_69ca828c474c8190a254d6499871eaff completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb39fef2e48190a6282c217c33c57a completed March 31, 2026, 3:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69f43ee693048190a8c7ecdf8724d3ec completed May 1, 2026, 5:49 a.m.
Created at: March 30, 2026, 5 p.m.