Triple

T7908277
Position Surface form Disambiguated ID Type / Status
Subject Pravdinsk E183630 entity
Predicate historicalName P65 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: [Pravdinsk, historicalName, Friedland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Friedland
Context triple: [Pravdinsk, historicalName, Friedland]
  • A. Friedland
    Friedland is a municipality in Lower Saxony, Germany, known for its historic border location and post-World War II refugee transit camp.
  • B. 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.
  • C. Bromberg
    Bromberg is the former German name for the city of Bydgoszcz, a major urban and industrial center in present-day north-central Poland.
  • D. Zeuthen
    Zeuthen is a municipality in Brandenburg, Germany, known for hosting a major campus of the DESY particle physics research center.
  • E. 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.
  • 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_69ca828dec0c81908b8f55a4dbbb53ff completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3a59de00819099f1ce02bb469e75 completed March 31, 2026, 3:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5bd0024c81909679a45612bcb1a7 completed March 31, 2026, 5:29 a.m.
Created at: March 30, 2026, 5:03 p.m.