Triple

T12083143
Position Surface form Disambiguated ID Type / Status
Subject Sorpe River E287732 entity
Predicate flowsThrough P225 FINISHED
Object Sundern E228422 NE 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: Sundern | Statement: [Sorpe River, flowsThrough, Sundern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sundern
Context triple: [Sorpe River, flowsThrough, Sundern]
  • A. Sundern chosen
    Sundern is a town in the Hochsauerland district of North Rhine-Westphalia, Germany, known for its proximity to the Sorpe Dam and the surrounding Sauerland recreational region.
  • B. Süddorf
    Süddorf is a small village on the North Sea island of Amrum in northern Germany, known for its traditional Frisian character and coastal surroundings.
  • C. Winsum
    Winsum is a historic village and former municipality in the Dutch province of Groningen, known for its old churches, windmills, and picturesque canals.
  • D. Nottuln
    Nottuln is a historic municipality in North Rhine-Westphalia, Germany, known for its medieval architecture and role in regional conflicts.
  • E. Teesdorf
    Teesdorf is a municipality in Lower Austria known for its motorsport testing facilities and rural setting south of Vienna.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d6ab4964708190850585628b287b0c completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915124e4c8190b0264c2a09e3c2f3 completed April 10, 2026, 3:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f66509208190b7206e78df41c2fe completed May 2, 2026, 1:04 p.m.
Created at: April 8, 2026, 9:48 p.m.