Triple

T1191635
Position Surface form Disambiguated ID Type / Status
Subject House of Oldenburg E25373 entity
Predicate hasMonarchIn P403 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: [House of Oldenburg, hasMonarchIn, Oldenburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oldenburg
Context triple: [House of Oldenburg, hasMonarchIn, 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. Bremerhaven
    Bremerhaven is a major German port city on the North Sea, known for its maritime industry, shipbuilding, and role as a key hub for trade and logistics.
  • C. Soest
    Soest is a historic town in North Rhine-Westphalia, Germany, known for its well-preserved medieval architecture and former significance as a Hanseatic trading center.
  • D. Lübeck
    Lübeck is a historic Hanseatic city in northern Germany renowned for its medieval architecture and long-standing role as a key trading hub on the Baltic Sea.
  • E. Lüneburg
    Lüneburg is a historic Hanseatic town in northern Germany renowned for its medieval architecture and former wealth from salt mining.
  • 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_69a49427d98881908646d6c63b8cea1e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bf15423481909cb3e661e58d3d94 completed March 1, 2026, 10:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69adb5ac8a2481908394095e9a6edc6a completed March 8, 2026, 5:45 p.m.
Created at: March 1, 2026, 7:45 p.m.