Triple

T7892496
Position Surface form Disambiguated ID Type / Status
Subject Disney Ambassador Hotel E183268 entity
Predicate hasRestaurant P4442 FINISHED
Object Hana
Hana is a Japanese restaurant located within Tokyo Disney Resort’s Disney Ambassador Hotel, offering themed dining to hotel guests and park visitors.
 E697346 NE FINISHED

How this triple was built (4 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: Hana | Statement: [Disney Ambassador Hotel, hasRestaurant, Hana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Hana
Context triple: [Disney Ambassador Hotel, hasRestaurant, Hana]
  • A. Hana
    Hana is a compassionate Canadian army nurse in Michael Ondaatje's novel "The English Patient," who cares for a badly burned man in an abandoned Italian villa during World War II.
  • B. Hana
    Hana is a small, remote town on the eastern coast of Maui, Hawaii, known for its lush landscapes, waterfalls, and the scenic Road to Hana.
  • C. Hana
    Hana is a person known primarily as the romantic partner of Kip.
  • D. Hana
    Hana is a common female given name of Hebrew origin, often associated with meanings like "grace" or "favor."
  • E. Harumi
    Harumi is a waterfront district in Tokyo’s Chūō ward known for its high-rise residential towers and role in the Tokyo 2020 Olympic and Paralympic Village.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Hana
Triple: [Disney Ambassador Hotel, hasRestaurant, Hana]
Generated description
Hana is a Japanese restaurant located within Tokyo Disney Resort’s Disney Ambassador Hotel, offering themed dining to hotel guests and park visitors.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Hana
Target entity description: Hana is a Japanese restaurant located within Tokyo Disney Resort’s Disney Ambassador Hotel, offering themed dining to hotel guests and park visitors.
  • A. Hana
    Hana is a compassionate Canadian army nurse in Michael Ondaatje's novel "The English Patient," who cares for a badly burned man in an abandoned Italian villa during World War II.
  • B. Hana
    Hana is a small, remote town on the eastern coast of Maui, Hawaii, known for its lush landscapes, waterfalls, and the scenic Road to Hana.
  • C. Hana
    Hana is a person known primarily as the romantic partner of Kip.
  • D. Hana
    Hana is a common female given name of Hebrew origin, often associated with meanings like "grace" or "favor."
  • E. Harumi
    Harumi is a waterfront district in Tokyo’s Chūō ward known for its high-rise residential towers and role in the Tokyo 2020 Olympic and Paralympic Village.
  • F. None of above. chosen

Provenance (5 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_69cb5ba51ee48190b654a931da2c049f completed March 31, 2026, 5:29 a.m.
NEDg Description generation batch_69cb5f1e84fc8190b535016cb69405b4 completed March 31, 2026, 5:43 a.m.
NED2 Entity disambiguation (via description) batch_69cb76a214488190b90e5db28511daa0 completed March 31, 2026, 7:24 a.m.
Created at: March 30, 2026, 5 p.m.