Triple

T7123432
Position Surface form Disambiguated ID Type / Status
Subject Fort Kongenstein E165999 entity
Predicate hasLanguageOfHistoricalAdministration P11893 FINISHED
Object Danish 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: Danish | Statement: [Fort Kongenstein, hasLanguageOfHistoricalAdministration, Danish]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasLanguageOfHistoricalAdministration
Context triple: [Fort Kongenstein, hasLanguageOfHistoricalAdministration, Danish]
  • A. historicallyDominantLanguageOfAdministrationIn chosen
    Indicates that a language has historically been the primary language used for official governance and administrative functions within a given place or political entity.
  • B. hasMajorityLanguageHistorically
    Indicates that a particular language has historically been the predominant or majority language within a given entity or region.
  • C. languageOfHistoricName
    Indicates the language in which a historic or former name of an entity is expressed.
  • D. historicallySpokenIn
    Indicates that a language was used for spoken communication in a particular place or region during a past historical period.
  • E. historicalLanguageRegion
    Indicates that a language was historically spoken or used within a particular geographic region, regardless of its current status there.
  • 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_69c6888350588190870cd552b427a1cd completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e64ab1f881908bc2468cc72d2544 completed March 27, 2026, 8:19 p.m.
PD Predicate disambiguation batch_69c6e1c7289881909f3b533c384f9ed4 completed March 27, 2026, 8 p.m.
Created at: March 27, 2026, 2:44 p.m.