Triple

T169481
Position Surface form Disambiguated ID Type / Status
Subject Universal Studios Japan E3086 entity
Predicate nearbyCity P350 FINISHED
Object Kobe E3089 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: Kobe | Statement: [Universal Studios Japan, nearbyCity, Kobe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kobe
Context triple: [Universal Studios Japan, nearbyCity, Kobe]
  • A. Kobe chosen
    Kobe is a major port city in Japan’s Kansai region, known for its scenic harbor setting, cosmopolitan atmosphere, and famous Kobe beef.
  • B. Port of Kobe
    The Port of Kobe is one of Japan’s major international seaports, serving as a key hub for container shipping and maritime trade in the Kansai region.
  • C. Yokohama
    Yokohama is Japan’s second-largest city and a major international port located just south of Tokyo.
  • D. Long Beach
    Long Beach is a coastal city in Southern California known for its busy port, waterfront attractions, and diverse urban community within the Los Angeles metropolitan area.
  • E. Riverside
    Riverside is a major inland city in Southern California known as the birthplace of the California citrus industry and a key center of the Inland Empire region.
  • 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_69a2524ce1e48190ab066bf72859f474 completed Feb. 28, 2026, 2:26 a.m.
NER Named-entity recognition batch_69a258b6f4f88190b1264bbbeb19a29e completed Feb. 28, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69a358763c10819085252de003a45435 completed Feb. 28, 2026, 9:04 p.m.
Created at: Feb. 28, 2026, 2:34 a.m.