Triple

T34615917
Position Surface form Disambiguated ID Type / Status
Subject Danish regions E888862 entity
Predicate mainCompetence P18508 FINISHED
Object hospital services 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: hospital services | Statement: [Danish regions, mainCompetence, hospital services]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: mainCompetence
Context triple: [Danish regions, mainCompetence, hospital services]
  • A. competenceArea chosen
    Indicates that one entity has a particular domain, field, or area in which it possesses competence, expertise, or responsibility.
  • B. definesCompetenceOf
    Indicates that one entity specifies, determines, or establishes the scope, level, or nature of another entity’s competence or capability.
  • C. competence
    Indicates that an entity has the ability, skill, or qualification to perform a task or fulfill a role effectively.
  • D. hasCompetence
    Indicates that an entity possesses the ability, skill, or qualification to perform a specific task or function effectively.
  • E. concurrentCompetenceArea
    Indicates that two or more competence areas are active or applicable at the same time in relation to the same context, task, or entity.
  • 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_69f349d584e08190b40b9f6281ad50c4 completed April 30, 2026, 12:23 p.m.
NER Named-entity recognition batch_69fd2839880c819099a7a89783f2270e completed May 8, 2026, 12:03 a.m.
PD Predicate disambiguation batch_69fd23dc5da48190ae8ba08947d34956 completed May 7, 2026, 11:44 p.m.
Created at: May 1, 2026, 2:03 a.m.