Triple

T27910814
Position Surface form Disambiguated ID Type / Status
Subject Stadtverwaltung von Groß-Berlin E705922 entity
Predicate appliesToTemporalExtent P51711 FINISHED
Object erste Hälfte des 20. Jahrhunderts 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: erste Hälfte des 20. Jahrhunderts | Statement: [Stadtverwaltung von Groß-Berlin, appliesToTemporalExtent, erste Hälfte des 20. Jahrhunderts]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: appliesToTemporalExtent
Context triple: [Stadtverwaltung von Groß-Berlin, appliesToTemporalExtent, erste Hälfte des 20. Jahrhunderts]
  • A. hasTemporalUse chosen
    Indicates that something is used, applicable, or valid only during a specific time or temporal interval.
  • B. hasTemporalDefinition
    Indicates that something is associated with a definition or specification that is constrained or characterized by time.
  • C. hasTemporalAttribute
    Indicates that an entity is associated with a specific temporal property or characteristic, such as time, duration, or period.
  • D. hasTemporalEnd
    Indicates that an event, state, or process concludes or terminates at a specific point or interval in time.
  • E. hasTemporalResolution
    Indicates that one entity specifies the level of temporal detail or granularity at which another entity’s data, observation, or process is measured or represented.
  • 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_69ef96b5aad08190be36a277c31e7004 completed April 27, 2026, 5:02 p.m.
NER Named-entity recognition batch_69fb3425666081908916fcbf3b5dd907 completed May 6, 2026, 12:29 p.m.
PD Predicate disambiguation batch_69fb2f5f3164819099429c2cc3d24e01 completed May 6, 2026, 12:09 p.m.
Created at: April 27, 2026, 6:49 p.m.