Triple

T21259107
Position Surface form Disambiguated ID Type / Status
Subject Warendorf district E523949 entity
Predicate containsMunicipality P852 FINISHED
Object Everswinkel NE NERFINISHED

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: Everswinkel | Statement: [Warendorf district, containsMunicipality, Everswinkel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Everswinkel
Context triple: [Warendorf district, containsMunicipality, Everswinkel]
  • A. Everswinkel chosen
    Everswinkel is a small municipality in western Germany known for its rural character and location in the Münsterland region of North Rhine-Westphalia.
  • B. Evertsen
    Evertsen is a Dutch surname historically associated with a prominent family of naval officers in the Dutch Republic.
  • C. Scherpenisse
    Scherpenisse is a village in the Dutch province of Zeeland, located on the island of Tholen.
  • D. Vezhof
    Vezhof is a constructed language associated with the Great Stallion setting, likely designed to reflect the culture and themes of that fictional world.
  • E. Reeshof
    Reeshof is a large residential district in the western part of Tilburg in the Netherlands, known for its modern housing developments and green spaces.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b5156d7881909bd4f83676590715 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e735e53df88190bd6024793a0ada08 completed April 21, 2026, 8:31 a.m.
Created at: April 16, 2026, 3:59 p.m.