Triple

T22736881
Position Surface form Disambiguated ID Type / Status
Subject Hamburg E562294 entity
Predicate hasPort P35 FINISHED
Object Port of Hamburg NE NERFINISHED

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: Port of Hamburg | Statement: [Hamburg, hasPort, Port of Hamburg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Port of Hamburg
Context triple: [Hamburg, hasPort, Port of Hamburg]
  • A. Port of Hamburg chosen
    The Port of Hamburg is Germany’s largest seaport and a major European logistics hub, known as the country’s “Gateway to the World.”
  • B. Port of Bremen
    The Port of Bremen is a major German river port complex on the Weser that serves as an important hub for maritime trade, logistics, and industry in northern Europe.
  • C. Port of Frankfurt
    The Port of Frankfurt is an inland river port complex on the Main River that serves as a key logistics and industrial hub for the city of Frankfurt am Main, Germany.
  • D. Port of Bremerhaven
    The Port of Bremerhaven is one of Europe’s major seaports and a key hub for container shipping and automobile exports on Germany’s North Sea coast.
  • E. Port of Cologne
    The Port of Cologne is a major inland port on the Rhine River that serves as a key logistics and transportation hub for trade and industry in western Germany.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e24550859c81908727d91efc3a81b4 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1796fc2a88190a4d86b421345b088 completed April 29, 2026, 3:22 a.m.
Created at: April 17, 2026, 3:22 p.m.