Triple

T18360616
Position Surface form Disambiguated ID Type / Status
Subject Shikina-en Garden E439903 entity
Predicate maintainedBy P86 FINISHED
Object City of Naha 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: City of Naha | Statement: [Shikina-en Garden, maintainedBy, City of Naha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Naha
Context triple: [Shikina-en Garden, maintainedBy, City of Naha]
  • A. City of Naha chosen
    The City of Naha is the capital and largest city of Okinawa Prefecture in Japan, known as a historic Ryukyuan cultural center and major regional port.
  • B. City of Ginowan
    The City of Ginowan is a municipality in central Okinawa, Japan, known for its coastal location, urban development, and proximity to U.S. military bases.
  • C. Gotemba City
    Gotemba City is a Japanese city in Shizuoka Prefecture near the southeastern base of Mount Fuji, known as a gateway for climbing and tourism around the mountain.
  • D. Kamishihoro
    Kamishihoro is a town in Hokkaido, Japan, known for its natural scenery, hot springs, and the historic Taushubetsu River Bridge within the Daisetsuzan mountain region.
  • E. Nanyo City
    Nanyo City is a municipality in northeastern Japan known for its hot springs, fruit production, and scenic rural landscapes.
  • 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_69d8b918221c8190a9f7b563d64ac677 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e516db045c8190b20c209225a53b9a completed April 19, 2026, 5:54 p.m.
Created at: April 10, 2026, 10:37 a.m.