Triple

T22789285
Position Surface form Disambiguated ID Type / Status
Subject Eslohe E564063 entity
Predicate hasNeighbouringMunicipality P224 FINISHED
Object Schmallenberg 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: Schmallenberg | Statement: [Eslohe, hasNeighbouringMunicipality, Schmallenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schmallenberg
Context triple: [Eslohe, hasNeighbouringMunicipality, Schmallenberg]
  • A. Schmallenberg chosen
    Schmallenberg is a small town in the Hochsauerland district of North Rhine-Westphalia, Germany, known for its picturesque landscapes and tourism in the Sauerland region.
  • B. Puumala
    Puumala is a Finnish municipality in the South Savo region, known for its scenic lakeside landscapes and popular summer cottages.
  • C. Vircava
    Vircava is a river in Latvia that serves as one of the tributaries feeding into the larger Lielupe River system.
  • D. Marheineke
    Marheineke is a German surname most notably associated with the 19th-century Protestant theologian Philipp Marheineke.
  • E. Marburg virus
    Marburg virus is a highly lethal filovirus that causes severe hemorrhagic fever in humans and nonhuman primates, similar to Ebola.
  • 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_69e2455500788190b4b33030461f3bbd completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17c3488708190812f7d2edac92184 completed April 29, 2026, 3:34 a.m.
Created at: April 17, 2026, 3:29 p.m.