Triple

T17758757
Position Surface form Disambiguated ID Type / Status
Subject Tama City E443311 entity
Predicate knownFor P22 FINISHED
Object Sanrio Puroland NE NERFINISHED

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: Sanrio Puroland | Statement: [Tama City, knownFor, Sanrio Puroland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sanrio Puroland
Context triple: [Tama City, knownFor, Sanrio Puroland]
  • A. Sanrio Puroland chosen
    Sanrio Puroland is an indoor theme park in Japan dedicated to Sanrio characters like Hello Kitty, featuring character shows, attractions, and themed dining.
  • B. Sanrio
    Sanrio is a Japanese company best known for creating and licensing cute character brands such as Hello Kitty and My Melody, featured on a wide range of merchandise and in themed attractions.
  • C. Kachidoki
    Kachidoki is a waterfront district in Tokyo’s Chūō ward known for its high-rise residential towers, proximity to the Sumida River, and convenient access to central Tokyo.
  • D. Takara
    Takara is a Japanese toy company best known for creating and producing Transformers and other popular action figures.
  • E. Yagiyama Benyland
    Yagiyama Benyland is an amusement park located in the Yagiyama area of Sendai, Japan, known for its family-friendly rides and scenic hilltop views.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9edf16c8190a59ebd245d378f4f completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48420ad188190aeb0f4ec1d23ee5c completed April 19, 2026, 7:28 a.m.
Created at: April 10, 2026, 10:10 a.m.