Triple

T20960010
Position Surface form Disambiguated ID Type / Status
Subject Hamburg S-Bahn E516213 entity
Predicate hasTerminus P388 FINISHED
Object Pinneberg 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: Pinneberg | Statement: [Hamburg S-Bahn, hasTerminus, Pinneberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pinneberg
Context triple: [Hamburg S-Bahn, hasTerminus, Pinneberg]
  • A. Pinneberg chosen
    Pinneberg is a town in northern Germany that serves as the administrative center of the district of the same name near Hamburg.
  • B. Lüneburg
    Lüneburg is a historic Hanseatic town in northern Germany renowned for its medieval architecture and former wealth from salt mining.
  • C. Bremervörde
    Bremervörde is a small town in Lower Saxony, northern Germany, situated between Hamburg and Bremen and known for its historic castle site and scenic location in the Elbe-Weser triangle.
  • D. Papenburg
    Papenburg is a German town in Lower Saxony best known for its historic canals and its large Meyer Werft shipyard, one of the world’s leading builders of cruise ships.
  • E. Harkstede
    Harkstede is a village in the Dutch province of Groningen, known for its rural character and proximity to the city of Groningen.
  • 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_69e0b4fde6c48190af1398e7e734629e completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6fb6e50988190a564d2aaf1a9bc54 completed April 21, 2026, 4:22 a.m.
Created at: April 16, 2026, 1:30 p.m.