Triple

T16694558
Position Surface form Disambiguated ID Type / Status
Subject Enz Valley E405680 entity
Predicate hasTown P847 FINISHED
Object Neuenbürg 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: Neuenbürg | Statement: [Enz Valley, hasTown, Neuenbürg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Neuenbürg
Context triple: [Enz Valley, hasTown, Neuenbürg]
  • A. Neuenbürg chosen
    Neuenbürg is a small historic town in the northern Black Forest region of Baden-Württemberg, Germany, known for its medieval castle and scenic river valley setting.
  • B. Günsberg
    Günsberg is a Swiss municipality located in the canton of Solothurn, known for its scenic setting near the Jura Mountains.
  • C. Nabburg
    Nabburg is a small historic town in Bavaria, Germany, known for its well-preserved medieval old town and scenic location along the Naab River.
  • D. Bötzingen
    Bötzingen is a municipality in southwestern Germany’s Baden-Württemberg region, situated near Freiburg in the Breisgau wine-growing area.
  • E. 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.
  • 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_69d8838db21081909589220fd71440a4 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37eacfa788190a8d2058f96c0d445 completed April 18, 2026, 12:53 p.m.
Created at: April 10, 2026, 5:19 a.m.