Triple

T6957740
Position Surface form Disambiguated ID Type / Status
Subject High Rhine E161287 entity
Predicate hasPart P35 FINISHED
Object Schaffhausen (city) E183831 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: Schaffhausen (city) | Statement: [High Rhine, hasPart, Schaffhausen (city)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schaffhausen (city)
Context triple: [High Rhine, hasPart, Schaffhausen (city)]
  • A. Schaffhausen chosen
    Schaffhausen is a historic town and capital of the canton of the same name in northern Switzerland, known for its well-preserved medieval old town and proximity to the Rhine Falls.
  • B. Schafhausen
    Schafhausen is a village and district of the town Weil der Stadt in the German state of Baden-Württemberg.
  • C. 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.
  • D. Hinwil
    Hinwil is a municipality and regional center in the Swiss canton of Zürich, known for its rural surroundings and as the home base of the Sauber Formula One team.
  • E. Türnich
    Türnich is a district of the town of Kerpen in North Rhine-Westphalia, Germany, known as a residential area within the Cologne metropolitan 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_69c68852a9a0819097797e31d492e273 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6dad0e52081908b524dc6a66bab01 completed March 27, 2026, 7:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69c922a0d2688190982714e2e409465d completed March 29, 2026, 1:01 p.m.
Created at: March 27, 2026, 2:29 p.m.