Triple

T6757265
Position Surface form Disambiguated ID Type / Status
Subject Ahaus town hall E154493 entity
Predicate seatOfGovernmentOf P761 FINISHED
Object Ahaus E28702 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: Ahaus | Statement: [Ahaus town hall, seatOfGovernmentOf, Ahaus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ahaus
Context triple: [Ahaus town hall, seatOfGovernmentOf, Ahaus]
  • A. Ahaus chosen
    Ahaus is a town in the district of Borken in North Rhine-Westphalia, western Germany, known for its historic castle and role as a regional administrative and cultural center.
  • B. Boppard
    Boppard is a historic town on the Rhine River in Germany, renowned for its well-preserved medieval architecture, wine culture, and scenic river landscapes.
  • C. Montabaur
    Montabaur is a historic town in western Germany’s Rhineland-Palatinate region, known for its distinctive hilltop castle and well-preserved old town.
  • D. Benrath
    Benrath is a German surname most notably associated with the late actor Martin Benrath.
  • E. Xanten
    Xanten is a historic town in western Germany known for its well-preserved Roman archaeological park and medieval architecture.
  • 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_69c6880fd5808190be684854081e27dd completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d1f76c9c81908c213772a54f1352 completed March 27, 2026, 6:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69c748a267488190bc7c5da9503b78c9 completed March 28, 2026, 3:18 a.m.
Created at: March 27, 2026, 2:11 p.m.