Triple

T6713028
Position Surface form Disambiguated ID Type / Status
Subject Kerpen E153193 entity
Predicate hasTwinTown P919 FINISHED
Object St. Vith E8397 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: St. Vith | Statement: [Kerpen, hasTwinTown, St. Vith]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: St. Vith
Context triple: [Kerpen, hasTwinTown, St. Vith]
  • A. St. Vith chosen
    St. Vith is a town in eastern Belgium that became a strategically important battleground during World War II, particularly noted for its role in the Battle of the Bulge.
  • B. Bastogne
    Bastogne is a town in southeastern Belgium best known for its strategic role and fierce fighting during World War II’s Battle of the Bulge.
  • C. Lannesdorf
    Lannesdorf is a residential subdistrict of the Bad Godesberg borough in the city of Bonn, Germany.
  • D. Beauvechain
    Beauvechain is a municipality in Walloon Brabant, Belgium, known for its rural character and the presence of a major Belgian Air Component base.
  • E. Armentières
    Armentières is a commune in northern France near the Belgian border, historically known for its textile industry and World War I significance.
  • 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_69c68809b4608190a2509ddb5ab87f05 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d121a92c8190a03f384a8aba84da completed March 27, 2026, 6:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69c700948788819087f9b466be337286 completed March 27, 2026, 10:11 p.m.
Created at: March 27, 2026, 2:07 p.m.