Triple

T3276126
Position Surface form Disambiguated ID Type / Status
Subject Brigach E68761 entity
Predicate flowsThrough P225 FINISHED
Object Donaueschingen E453611 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: Donaueschingen | Statement: [Brigach, flowsThrough, Donaueschingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Donaueschingen
Context triple: [Brigach, flowsThrough, 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. 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.
  • C. Offenburg
    Offenburg is a city in southwestern Germany’s Baden-Württemberg state, known as a regional economic and transport hub near the French border in the Upper Rhine region.
  • D. Schongau
    Schongau is a historic Bavarian town in southern Germany known for its well-preserved medieval old town and location along the Romantic Road.
  • E. Biberach an der Riß
    Biberach an der Riß is a historic town in the German state of Baden-Württemberg, known for its well-preserved medieval old town and traditional Swabian culture.
  • 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_69ad859b54f881909bf530d549caf2fd completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb0110f1c8190ae60708b686cbbf9 completed March 8, 2026, 5:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69bde0234b6481908dcf37da32cf856b completed March 21, 2026, 12:02 a.m.
Created at: March 8, 2026, 3:10 p.m.