Triple

T17927085
Position Surface form Disambiguated ID Type / Status
Subject Amberg-Sulzbach E448225 entity
Predicate contains P35 FINISHED
Object Sulzbach-Rosenberg 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: Sulzbach-Rosenberg | Statement: [Amberg-Sulzbach, contains, Sulzbach-Rosenberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sulzbach-Rosenberg
Context triple: [Amberg-Sulzbach, contains, Sulzbach-Rosenberg]
  • A. Sulzbach-Rosenberg chosen
    Sulzbach-Rosenberg is a historic town in Bavaria, Germany, known for its medieval heritage and former importance as a regional administrative and industrial center.
  • B. Odelzhausen
    Odelzhausen is a municipality in Bavaria, Germany, known for its historic castle and location along the Autobahn between Munich and Augsburg.
  • C. Gernsbach
    Gernsbach is a historic town in southwestern Germany’s Black Forest region, known for its medieval old town and picturesque setting along the Murg River.
  • D. Grafenrheinfeld
    Grafenrheinfeld is a small Bavarian town best known for hosting the former Grafenrheinfeld nuclear power plant on the Main River in northern Germany.
  • E. Sulzheim
    Sulzheim is a small municipality in the Schweinfurt district of Lower Franconia in northern Bavaria, Germany.
  • 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_69d8b9f79d14819095540856928f0e25 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e4a54f29a88190b035d8473765bde5 completed April 19, 2026, 9:50 a.m.
Created at: April 10, 2026, 10:20 a.m.