Triple

T16213520
Position Surface form Disambiguated ID Type / Status
Subject Creutzwald E393524 entity
Predicate neighbouringCommune P33892 FINISHED
Object Wallerfangen E1082527 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: Wallerfangen | Statement: [Creutzwald, neighbouringCommune, Wallerfangen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wallerfangen
Context triple: [Creutzwald, neighbouringCommune, Wallerfangen]
  • A. Wallerfangen chosen
    Wallerfangen is a municipality in the Saarland region of western Germany, near the French border, known for its rural character and proximity to the town of Saarlouis.
  • B. Falkenstein
    Falkenstein is a district of the spa town Königstein im Taunus in Hesse, Germany, known for its scenic location in the Taunus mountains and historic castle ruins.
  • C. Oberfell
    Oberfell is a small municipality in western Germany situated along the Moselle River within the state of Rhineland-Palatinate.
  • D. Wildenberg
    Wildenberg is a small municipality in the Kelheim district of Lower Bavaria, Germany, known for its rural character and agricultural surroundings.
  • E. Wiedensahl
    Wiedensahl is a small village in Lower Saxony, Germany, best known as the birthplace of the humorist and illustrator Wilhelm Busch.
  • 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_69d87f1f5bd08190bd01cac0d5b9d2ef completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e227f393e08190be93400d754f0a2d completed April 17, 2026, 12:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a000794e6c881909c4521e4dd031971 completed May 10, 2026, 4:20 a.m.
Created at: April 10, 2026, 5:03 a.m.