Triple

T1753634
Position Surface form Disambiguated ID Type / Status
Subject German-speaking Belgium E38502 entity
Predicate containsSettlement P847 FINISHED
Object Büllingen E51882 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: Büllingen | Statement: [German-speaking Belgium, containsSettlement, Büllingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Büllingen
Context triple: [German-speaking Belgium, containsSettlement, Büllingen]
  • A. Büllingen chosen
    Büllingen is a municipality in eastern Belgium’s German-speaking Community, known for its rural landscape and proximity to the historically significant Elsenborn Ridge.
  • B. Boblingen
    Böblingen is a town in the German state of Baden-Württemberg, known for its automotive industry presence and proximity to Stuttgart.
  • C. Hunspach
    Hunspach is a picturesque village in northeastern France’s Alsace region, noted for its traditional half-timbered houses and designation as one of the “Most Beautiful Villages of France.”
  • D. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • E. Wüllen
    Wüllen is a district of the town of Ahaus in North Rhine-Westphalia, Germany, known for its rural character within the Münsterland 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_69a8862bdb2081908aefe831c8aa8017 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa64169c508190a33074fb06e9c755 completed March 6, 2026, 5:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69adfb98fee88190804f368b484c7305 completed March 8, 2026, 10:43 p.m.
Created at: March 4, 2026, 7:31 p.m.