Triple

T7890042
Position Surface form Disambiguated ID Type / Status
Subject Hamburg, Arkansas E183204 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, Arkansas, namedAfter, Hamburg, Germany]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hamburg, Germany
Context triple: [Hamburg, Arkansas, 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_69ca828c474c8190a254d6499871eaff completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb39ecb700819091c1bdfa95349d36 completed March 31, 2026, 3:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5b9f47cc8190a6f9fc087010ad96 completed March 31, 2026, 5:29 a.m.
Created at: March 30, 2026, 5 p.m.