Triple

T15610916
Position Surface form Disambiguated ID Type / Status
Subject Eschweiler E375285 entity
Predicate hasNeighbouringMunicipality P224 FINISHED
Object Alsdorf E845345 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: Alsdorf | Statement: [Eschweiler, hasNeighbouringMunicipality, Alsdorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alsdorf
Context triple: [Eschweiler, hasNeighbouringMunicipality, Alsdorf]
  • A. Alsdorf chosen
    Alsdorf is a town in western Germany’s North Rhine-Westphalia, historically shaped by coal mining and now part of the Aachen city region.
  • B. Tasdorf
    Tasdorf is a small municipality in northern Germany notable as the birthplace of the 19th-century opera composer Giacomo Meyerbeer.
  • C. Aulendorf
    Aulendorf is a small town in the Upper Swabia region of southern Germany, known for its historic castle and spa facilities.
  • D. Sierksdorf
    Sierksdorf is a small coastal municipality in northern Germany, known for its Baltic Sea beaches and the Hansa-Park amusement park.
  • E. Porschdorf
    Porschdorf is a village in Saxony, Germany, that forms part of the spa town and municipality of Bad Schandau in the Saxon Switzerland region.
  • 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_69d85ccf2794819096cda4cbcb02d478 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e8148a0819087d6d69cc84487ca completed April 16, 2026, 2:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffb0335a0c8190ade4c2f78df3d113 completed May 9, 2026, 10:07 p.m.
Created at: April 10, 2026, 4:13 a.m.