Triple

T13138031
Position Surface form Disambiguated ID Type / Status
Subject Okertal E312136 entity
Predicate near P350 FINISHED
Object Altenau E216207 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: Altenau | Statement: [Okertal, near, Altenau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Altenau
Context triple: [Okertal, near, Altenau]
  • A. Altenau chosen
    Altenau is a small town in Germany’s Harz Mountains, historically known as a mining and spa resort surrounded by dense forests and mountain landscapes.
  • B. Altenkunstadt
    Altenkunstadt is a market town in Upper Franconia, Bavaria, Germany, situated on the river Main and known for its historic center and regional textile and shoe industries.
  • C. Altenstadt
    Altenstadt is a small Bavarian municipality in southern Germany, situated within the rural district of Weilheim-Schongau.
  • D. Altenkirchen
    Altenkirchen is a small town in the state of Rhineland-Palatinate in western Germany, known as a local administrative and commercial center in the Westerwald region.
  • E. Albershausen
    Albershausen is a small municipality in the German state of Baden-Württemberg, located in the Göppingen district in southern Germany.
  • 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_69d806a9fe888190b081e2d9ea665d6c completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d981b6a4348190b9922ed255759078 completed April 10, 2026, 11:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7546b9ae081909f97fc4a06b8f927 completed May 3, 2026, 1:58 p.m.
Created at: April 9, 2026, 9:09 p.m.