Triple

T10318392
Position Surface form Disambiguated ID Type / Status
Subject Channel Dash E242077 entity
Predicate shipDestination P1522 FINISHED
Object Brunsbüttel E607908 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: Brunsbüttel | Statement: [Channel Dash, shipDestination, Brunsbüttel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brunsbüttel
Context triple: [Channel Dash, shipDestination, Brunsbüttel]
  • A. Brunsbüttel chosen
    Brunsbüttel is a German port town at the western entrance of the Kiel Canal on the North Sea coast of Schleswig-Holstein.
  • B. Fuhlsbüttel
    Fuhlsbüttel is a district in the northern German city of Hamburg best known for hosting the city’s international airport.
  • C. Hamburg-Finkenwerder
    Hamburg-Finkenwerder is a district of Hamburg, Germany, known for its historic and ongoing role in shipbuilding and aviation industries along the River Elbe.
  • D. Nittendorf
    Nittendorf is a municipality in the Upper Palatinate region of Bavaria, Germany, situated west of the city of Regensburg.
  • E. Norderstedt
    Norderstedt is a city in northern Germany that forms part of the Hamburg metropolitan area and is one of the larger urban centers 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_69d381ac38808190a8ca7457c85b625b completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4dfc1b0488190ac04da58a4987da0 completed April 7, 2026, 10:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69d75036ed008190aee48695ad7f857d completed April 9, 2026, 7:07 a.m.
Created at: April 6, 2026, 11:49 a.m.