Triple

T20061908
Position Surface form Disambiguated ID Type / Status
Subject Gäubahn corridor E499496 entity
Predicate passesThrough P225 FINISHED
Object Donaueschingen NE NERFINISHED

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: Donaueschingen | Statement: [Gäubahn corridor, passesThrough, Donaueschingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Donaueschingen
Context triple: [Gäubahn corridor, passesThrough, Donaueschingen]
  • A. Donaueschingen chosen
    Donaueschingen is a town in southwestern Germany, in the Black Forest region of Baden-Württemberg, known as one of the sources of the Danube River.
  • B. Ittlingen
    Ittlingen is a small municipality in the German state of Baden-Württemberg, located within the Heilbronn region.
  • C. Metzingen
    Metzingen is a town in the German state of Baden-Württemberg, known for its Swabian heritage and large outlet shopping district.
  • D. Elchingen
    Elchingen is a municipality in southern Germany, historically notable as the site of a major Napoleonic victory during the War of the Third Coalition.
  • E. Schwäbisch Gmünd
    Schwäbisch Gmünd is a historic town in the German state of Baden-Württemberg, known for its medieval architecture and long tradition of metalworking and jewelry craftsmanship.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da6276bcf48190aabbf279192a5fb4 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66376f2d4819081b9e1b265650e5b completed April 20, 2026, 5:33 p.m.
Created at: April 11, 2026, 3:39 p.m.