Triple

T7953989
Position Surface form Disambiguated ID Type / Status
Subject House of Oldenburg-Eutin E184683 entity
Predicate seat P75 FINISHED
Object Eutin E631963 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: Eutin | Statement: [House of Oldenburg-Eutin, seat, Eutin]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Eutin
Context triple: [House of Oldenburg-Eutin, seat, Eutin]
  • A. Eutin chosen
    Eutin is a historic town in northern Germany’s Schleswig-Holstein region, known for its picturesque lakeside setting, castle, and cultural festivals.
  • B. Halberstadt
    Halberstadt is a historic town in the German state of Saxony-Anhalt, known for its medieval architecture and role as a former episcopal seat.
  • C. Lankwitz
    Lankwitz is a residential locality in the southwestern part of Berlin, known for its quiet neighborhoods, green spaces, and mix of historic and modern architecture.
  • D. Lauenburg
    Lauenburg is a historic town in northern Germany situated on the banks of the Elbe River.
  • E. Magdeburg
    Magdeburg is a historic city in central Germany, known for its medieval cathedral, role as a major trading and industrial center, and location on the Elbe River.
  • 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_69ca8292cba881908a64427b938dac47 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb3b5f74308190aa63a22c3d5feacc completed March 31, 2026, 3:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccec8cfa80819082bc79645f33e18f completed April 1, 2026, 9:59 a.m.
Created at: March 30, 2026, 5:10 p.m.