Triple

T1367039
Position Surface form Disambiguated ID Type / Status
Subject Havel River E30026 entity
Predicate passesThrough P225 FINISHED
Object Oranienburg E217564 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: Oranienburg | Statement: [Havel River, passesThrough, Oranienburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oranienburg
Context triple: [Havel River, passesThrough, Oranienburg]
  • A. Oranienburg chosen
    Oranienburg is a town in Brandenburg, Germany, historically known as the site of the Nazi Sachsenhausen concentration camp.
  • B. Dessau
    Dessau is a German city best known for its association with the Bauhaus movement and its iconic modernist architecture.
  • C. Neustrelitz
    Neustrelitz is a town in northeastern Germany known for hosting a key research center of the German Aerospace Center (DLR), particularly focused on satellite data and space-related technologies.
  • D. 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.
  • E. Wernigerode
    Wernigerode is a picturesque German town in Saxony-Anhalt known for its colorful half-timbered houses, medieval castle, and location on the northern slopes of the Harz Mountains.
  • 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_69a498f912008190a376a98b207b2071 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c2d33d2081908008494b5f56bf56 completed March 1, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae26d7583c8190b84127ad2e5ca4c1 completed March 9, 2026, 1:48 a.m.
Created at: March 1, 2026, 7:57 p.m.