Triple

T7616021
Position Surface form Disambiguated ID Type / Status
Subject Jägerndorf E172362 entity
Predicate hasGermanName P1435 FINISHED
Object Jägerndorf E172362 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: Jägerndorf | Statement: [Jägerndorf, hasGermanName, Jägerndorf]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jägerndorf
Context triple: [Jägerndorf, hasGermanName, Jägerndorf]
  • A. Jägerndorf chosen
    Jägerndorf is a historic Silesian town (now Krnov in the Czech Republic) known for its strategic and political significance in Central European history.
  • B. Biendorf
    Biendorf is a small municipality in northern Germany notable as the birthplace of German Field Marshal Helmuth von Moltke the Younger.
  • C. Eugendorf
    Eugendorf is a market town in the Austrian state of Salzburg, known for its proximity to the city of Salzburg and its location in the scenic Salzkammergut region.
  • D. Zirndorf
    Zirndorf is a town in the Bavarian region of Germany, known for its proximity to Nuremberg and its mix of residential areas and light industry.
  • E. Hubersdorf
    Hubersdorf is a small municipality located in the canton of Solothurn in northwestern Switzerland.
  • 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_69c6994f50808190ba228764bb422417 completed March 27, 2026, 2:50 p.m.
NER Named-entity recognition batch_69c6fa4569c88190b2968403a24e7882 completed March 27, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8d69516a88190912a9574aef3d1f8 completed March 29, 2026, 7:36 a.m.
Created at: March 27, 2026, 3:55 p.m.