Triple

T6040508
Position Surface form Disambiguated ID Type / Status
Subject Hamburg, New York E134530 entity
Predicate namedAfter P63 FINISHED
Object Hamburg, Germany E7419 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: Hamburg, Germany | Statement: [Hamburg, New York, namedAfter, Hamburg, Germany]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hamburg, Germany
Context triple: [Hamburg, New York, namedAfter, Hamburg, Germany]
  • A. Hamburg-Finkenwerder, Germany
    Hamburg-Finkenwerder, Germany is an industrial district of Hamburg best known for its large Airbus manufacturing and assembly facilities.
  • B. Hamburg chosen
    Hamburg is Germany’s second-largest city and a major northern European port and cultural center on the River Elbe.
  • C. Hamm, Germany
    Hamm is a city in the German state of North Rhine-Westphalia, known as an industrial and transportation hub in the eastern Ruhr area.
  • D. Brunswick, Germany
    Brunswick, Germany is a historic city in Lower Saxony known for its medieval architecture, former status as a ducal residence, and role as an important commercial and cultural center in northern Germany.
  • E. Oldenburg, Germany
    Oldenburg, Germany is a historic city in northwestern Germany known for its former status as a grand duchy’s capital and its well-preserved old town.
  • 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_69c00875db5c819099dd5bb833ec43c2 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c056cf82d481909d5161fe3643e7ed completed March 22, 2026, 8:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c1357027388190beef9b9d9f5e37f6 completed March 23, 2026, 12:43 p.m.
Created at: March 22, 2026, 4:08 p.m.