Triple

T11877761
Position Surface form Disambiguated ID Type / Status
Subject Breisgau E282574 entity
Predicate hasCity P316 FINISHED
Object Emmendingen E730728 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: Emmendingen | Statement: [Breisgau, hasCity, Emmendingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emmendingen
Context triple: [Breisgau, hasCity, Emmendingen]
  • A. Emmendingen chosen
    Emmendingen is a town in southwestern Germany’s Baden-Württemberg state, known for its historic old town and location near Freiburg in the Breisgau region.
  • B. Emmering
    Emmering is a small municipality in Upper Bavaria, Germany, located in the Fürstenfeldbruck district west of Munich.
  • C. Hodenhagen
    Hodenhagen is a small municipality in Lower Saxony, Germany, known for its rural setting along the Aller River and proximity to attractions like the Serengeti Park safari zoo.
  • D. Werthhoven
    Werthhoven is a village-level district within the municipality of Wachtberg in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
  • E. Allmendingen
    Allmendingen is a small Swiss municipality in the canton of Bern, situated within the Bern-Mittelland 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_69d6ab2945d081908a5851c916cbcfb5 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8be1b6a5c81909a18c54205dda09c completed April 10, 2026, 9:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69f281d8c65081908ebaf4bff5670c47 completed April 29, 2026, 10:10 p.m.
Created at: April 8, 2026, 9:44 p.m.