Triple

T31372243
Position Surface form Disambiguated ID Type / Status
Subject F-WB E800193 entity
Predicate hasUniquenessScope P72877 FINISHED
Object Frankfurt public transport stations 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: Frankfurt public transport stations | Statement: [F-WB, hasUniquenessScope, Frankfurt public transport stations]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasUniquenessScope
Context triple: [F-WB, hasUniquenessScope, Frankfurt public transport stations]
  • A. hasUniqueness
    Indicates that something possesses a distinctive or one-of-a-kind quality that sets it apart from others.
  • B. isNonUniqueGlobally
    Indicates that the referenced item is not guaranteed to be unique across the entire global scope or system.
  • C. isUniqueWithinScheme chosen
    Indicates that an entity is the only one with its particular identifying characteristics within a given scheme or classification system.
  • D. typeOfUniqueness
    Indicates that one entity’s uniqueness is characterized, classified, or constrained by the specific kind or mode of uniqueness associated with another entity.
  • E. uniquenessCondition
    Indicates that a specified element, value, or combination of attributes must be unique within a given set, context, or domain, with no duplicates allowed.
  • 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_69f224e6b7448190ac6bf97ad7364160 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f7979a073881909a4fde2558e6b6f3 completed May 3, 2026, 6:44 p.m.
PD Predicate disambiguation batch_69f7961550f88190b7bb8a9155458b54 completed May 3, 2026, 6:38 p.m.
Created at: April 29, 2026, 9:18 p.m.