Triple

T2443049
Position Surface form Disambiguated ID Type / Status
Subject German occupation of Denmark E53322 entity
Predicate policyFeature P26219 FINISHED
Object maintenance of Danish government and monarchy until 1943 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: maintenance of Danish government and monarchy until 1943 | Statement: [German occupation of Denmark, policyFeature, maintenance of Danish government and monarchy until 1943]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: policyFeature
Context triple: [German occupation of Denmark, policyFeature, maintenance of Danish government and monarchy until 1943]
  • A. policyCharacteristic chosen
    Indicates that a policy possesses a particular attribute, feature, or quality that characterizes how it is defined or operates.
  • B. policyTool
    Indicates that an entity is a tool, mechanism, or instrument used to design, implement, or enforce a policy.
  • C. policyName
    Indicates the specific name or title assigned to a policy associated with an entity.
  • D. policyLevel
    Indicates the degree or tier of strictness, scope, or priority associated with a given policy.
  • E. protectsFeature
    Indicates that one entity safeguards, preserves, or defends a particular feature or characteristic of another 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_69ab495b6dac8190ac82661aa1452222 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abcabf477081908512df63ac1a6414 completed March 7, 2026, 6:50 a.m.
PD Predicate disambiguation batch_69abc5ad8e588190b97c4cd7cf575043 completed March 7, 2026, 6:29 a.m.
Created at: March 6, 2026, 9:43 p.m.