Triple

T4236842
Position Surface form Disambiguated ID Type / Status
Subject Albrecht von Wallenstein E94713 entity
Predicate residence P75 FINISHED
Object Friedland E214227 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: Friedland | Statement: [Albrecht von Wallenstein, residence, Friedland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Friedland
Context triple: [Albrecht von Wallenstein, residence, Friedland]
  • A. Friedland chosen
    Friedland is a town in present-day Pravdinsk, Russia, historically notable as the site of the decisive 1807 Napoleonic battle between French and Russian forces.
  • B. Friedland
    Friedland is a municipality in Lower Saxony, Germany, known for its historic border location and post-World War II refugee transit camp.
  • C. Leutenberg
    Leutenberg is a small town in the German state of Thuringia, known for its location in the Thuringian Slate Mountains and its historical sites.
  • D. Biebrich
    Biebrich is a district of Wiesbaden in the German state of Hesse, historically known as an independent town on the Rhine and the site of the Baroque Biebrich Palace.
  • E. Friedberg
    Friedberg is a historic German town in the state of Hesse, known for its medieval fortifications and strategic importance during the Seven Years' War.
  • 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_69b34537cc6481909cd0a96acbb33ef7 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b34e7422a88190955f5f4347fa80d2 completed March 12, 2026, 11:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5b77632d08190ab7c12986e2cee61 completed March 14, 2026, 7:31 p.m.
Created at: March 12, 2026, 11:05 p.m.