Triple

T1279092
Position Surface form Disambiguated ID Type / Status
Subject Tokyo Bay E27281 entity
Predicate shorelineIncludes P26675 FINISHED
Object Tokyo Waterfront City E64227 NE FINISHED

How this triple was built (3 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: Tokyo Waterfront City | Statement: [Tokyo Bay, shorelineIncludes, Tokyo Waterfront City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tokyo Waterfront City
Context triple: [Tokyo Bay, shorelineIncludes, Tokyo Waterfront City]
  • A. Shibuya Mark City
    Shibuya Mark City is a large commercial complex in Tokyo’s Shibuya district, featuring offices, a hotel, and a shopping and dining mall directly connected to Shibuya Station.
  • B. Shibuya Hikarie
    Shibuya Hikarie is a major high-rise commercial complex in Tokyo known for its shopping, dining, cultural facilities, and direct connection to Shibuya Station.
  • C. Odaiba chosen
    Odaiba is a popular high-tech entertainment and shopping district built on a man-made island in Tokyo Bay.
  • D. Tempozan Harbor Village
    Tempozan Harbor Village is a waterfront shopping and entertainment complex in Osaka, Japan, known for attractions like the Tempozan Ferris Wheel and its proximity to the Osaka Aquarium Kaiyukan.
  • E. Tokyo Center
    Tokyo Center is an urban satellite campus of Kansai University located in Tokyo, primarily used for specialized programs, research activities, and academic exchanges.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: shorelineIncludes
Context triple: [Tokyo Bay, shorelineIncludes, Tokyo Waterfront City]
  • A. hasShorelineUse
    Indicates that a geographic area or property is used for a particular type of activity or purpose along its shoreline.
  • B. shoreType
    Indicates the kind or classification of a shoreline associated with a body of water or coastal area.
  • C. shorelineLength
    Indicates the total measured extent of a land area’s boundary where it meets a body of water.
  • D. formsShorelineOf
    Indicates that one geographic feature constitutes or defines the boundary or edge (shoreline) of a body of water.
  • E. hasShoreOn
    Indicates that one geographic entity borders or is directly adjacent to the shore of another body of water.
  • 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_69a496d3710c8190955dee8bc0dacb50 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c092eb688190bf42bbd59e4ff289 completed March 1, 2026, 10:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69acde0ccff4819092948c249e0cb39b completed March 8, 2026, 2:25 a.m.
PD Predicate disambiguation batch_69a4bee276d8819092f71c5a1140bb61 completed March 1, 2026, 10:34 p.m.
PDg Predicate description generation batch_69a4bf60545c8190901ccfb2cb7c4b41 completed March 1, 2026, 10:36 p.m.
Created at: March 1, 2026, 7:50 p.m.