Triple

T14678416
Position Surface form Disambiguated ID Type / Status
Subject Northern Switzerland E344708 entity
Predicate containsTown P847 FINISHED
Object Koblenz (Switzerland) E633931 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: Koblenz (Switzerland) | Statement: [Northern Switzerland, containsTown, Koblenz (Switzerland)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Koblenz (Switzerland)
Context triple: [Northern Switzerland, containsTown, Koblenz (Switzerland)]
  • A. Koblenz (Aargau) chosen
    Koblenz (Aargau) is a small Swiss municipality in the canton of Aargau, situated at the confluence of the Aare and Rhine rivers near the German border.
  • B. Grenchen
    Grenchen is a Swiss town in the canton of Solothurn known for its watchmaking industry and location at the foot of the Jura Mountains.
  • C. Kilchberg
    Kilchberg is a municipality on the shores of Lake Zurich in Switzerland, known for its scenic residential character and as the home of the Lindt & Sprüngli chocolate factory.
  • D. Oetwil an der Limmat
    Oetwil an der Limmat is a municipality in the canton of Zurich in Switzerland, situated along the Limmat River in the Limmat Valley region.
  • E. Bremgarten
    Bremgarten is a historic Swiss town in the canton of Aargau, known for its well-preserved medieval old town and scenic riverside setting.
  • 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_69d822e34b348190ada4d1cdb6c7c226 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb567c2b88190a9639e61b6fba7df completed April 14, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fde17e5a1c8190b1bf5565eab9d519 completed May 8, 2026, 1:13 p.m.
Created at: April 10, 2026, 1:27 a.m.