Triple

T1146956
Position Surface form Disambiguated ID Type / Status
Subject University of Fribourg E23587 entity
Predicate hasCityCharacteristic P9356 FINISHED
Object located in a bilingual city 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: located in a bilingual city | Statement: [University of Fribourg, hasCityCharacteristic, located in a bilingual city]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCityCharacteristic
Context triple: [University of Fribourg, hasCityCharacteristic, located in a bilingual city]
  • A. hasUrbanFeature
    Indicates that a place or area possesses a specific urban element or infrastructure feature (such as roads, parks, or buildings) as part of its built environment.
  • B. neighborhoodCharacteristic chosen
    Indicates that a particular characteristic, feature, or quality is associated with or describes a given neighborhood.
  • C. hasSuburbanCharacter
    Indicates that something possesses qualities or features typically associated with suburban areas, such as lower density, residential focus, and car-oriented development.
  • D. hasGeographyCharacteristic
    Indicates that an entity possesses a specific geographical feature, property, or attribute.
  • E. coversCity
    Indicates that one entity extends over, includes, or geographically encompasses the area of a specified city.
  • 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_69a493ef399c8190b04b9146d2314f59 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bd0bed00819091d71983d787a030 completed March 1, 2026, 10:26 p.m.
PD Predicate disambiguation batch_69a4bb4ee3988190ac89c5ae5b10e316 completed March 1, 2026, 10:18 p.m.
Created at: March 1, 2026, 7:44 p.m.