Triple

T12402628
Position Surface form Disambiguated ID Type / Status
Subject Ulm–Augsburg railway E296295 entity
Predicate hasStation P35 FINISHED
Object Dinkelscherben E801079 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: Dinkelscherben | Statement: [Ulm–Augsburg railway, hasStation, Dinkelscherben]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dinkelscherben
Context triple: [Ulm–Augsburg railway, hasStation, Dinkelscherben]
  • A. Dinkelscherben chosen
    Dinkelscherben is a municipality in the Swabian region of Bavaria in southern Germany.
  • B. Baar-Ebenhausen
    Baar-Ebenhausen is a Bavarian municipality in southern Germany known for its residential character and location along the Ilm River.
  • C. Mausberg
    Mausberg was an American West Coast rapper from Compton, California, known for his collaborations with DJ Quik before his life was tragically cut short.
  • D. Zell im Wiesental
    Zell im Wiesental is a small town in the Black Forest region of southwestern Germany, known as the birthplace of Constanze Mozart, the wife of composer Wolfgang Amadeus Mozart.
  • E. Biedenkopf
    Biedenkopf is a small historic town in the German state of Hesse, known for its medieval old town and hilltop castle.
  • 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_69d6ad9f464c81909db36d7e96e34b9e completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d477004819095e65ef6f70c69d9 completed April 10, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63484c6808190a71d24f8ee3a7e15 completed May 2, 2026, 5:29 p.m.
Created at: April 8, 2026, 9:55 p.m.