Triple

T13316589
Position Surface form Disambiguated ID Type / Status
Subject Kintetsu Department Store E317202 entity
Predicate flagshipBuildingHeightRank P31595 FINISHED
Object one of the tallest buildings in Japan LITERAL 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: one of the tallest buildings in Japan | Statement: [Kintetsu Department Store, flagshipBuildingHeightRank, one of the tallest buildings in Japan]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: flagshipBuildingHeightRank
Context triple: [Kintetsu Department Store, flagshipBuildingHeightRank, one of the tallest buildings in Japan]
  • A. tallestBuildingIn
    Indicates that one entity is the tallest building located within the area or region specified by the other entity.
  • B. rankAmongTallestBuildings chosen
    Indicates that one building is among the tallest buildings within a specified group, area, or category.
  • C. buildingHeight
    Indicates the vertical extent or height measurement of a building.
  • D. rankInCityByHeight
    Indicates the relative ordering of entities within a specific city based on their height, such as which is tallest, second tallest, and so on.
  • E. buildingHeightContext
    Indicates the contextual or situational factors under which a building’s height is defined, measured, or interpreted.
  • F. None of above.

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_69d806b4d62c81908d4ced1665414be5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99cfdc9388190af1fdd3cd4717bd8 completed April 11, 2026, 12:59 a.m.
PD Predicate disambiguation batch_69d98f6babd88190a5d529df9584b9a4 completed April 11, 2026, 12:01 a.m.
Created at: April 9, 2026, 9:29 p.m.