Triple

T9975982
Position Surface form Disambiguated ID Type / Status
Subject Duke of Bremen-Verden E196327 entity
Predicate borderedBy P224 FINISHED
Object Oldenburg E73235 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: Oldenburg | Statement: [Duke of Bremen-Verden, borderedBy, Oldenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oldenburg
Context triple: [Duke of Bremen-Verden, borderedBy, Oldenburg]
  • A. Oldenburg chosen
    Oldenburg is a historic university city in northwestern Germany known for its cultural heritage and role as a regional economic center.
  • B. Oldenburg
    Oldenburg is a historic European noble house that ruled various territories in Denmark, Norway, and northern Germany and provided numerous monarchs to several European thrones.
  • C. Friedrichstadt
    Friedrichstadt is a historic canal town in northern Germany’s Schleswig-Holstein, known for its Dutch-style architecture and waterways.
  • D. Flensburg
    Flensburg is a historic port city in northern Germany near the Danish border, known for its maritime heritage and role as a regional administrative and cultural center in Schleswig-Holstein.
  • E. Itzehoe
    Itzehoe is a historic town in northern Germany known for its medieval origins and role as a regional center in the state of Schleswig-Holstein.
  • 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_69ca82eea2b88190a0e511d21a31f386 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb84b47308190aa2f94fa7320cdc3 completed April 2, 2026, 12:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69d299e3d5fc8190a953be3ebd8250e6 completed April 5, 2026, 5:20 p.m.
Created at: March 30, 2026, 8:48 p.m.