Triple

T9025407
Position Surface form Disambiguated ID Type / Status
Subject South Beach (Südstrand) E216034 entity
Predicate near P350 FINISHED
Object Wilhelmshaven city center E41561 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: Wilhelmshaven city center | Statement: [South Beach (Südstrand), near, Wilhelmshaven city center]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wilhelmshaven city center
Context triple: [South Beach (Südstrand), near, Wilhelmshaven city center]
  • A. Wilhelmshaven chosen
    Wilhelmshaven is a coastal city in northwestern Germany known for its major naval base and port on the North Sea.
  • B. Aurich
    Aurich is a historic town in northwestern Germany that serves as one of the principal urban centers of the East Frisia region in Lower Saxony.
  • C. Port of Wilhelmshaven
    The Port of Wilhelmshaven is Germany’s only deep-water container port and a major North Sea harbor handling crude oil, containers, and naval operations.
  • D. Cuxhaven
    Cuxhaven is a German port city on the North Sea coast that historically served as an important naval and maritime hub.
  • E. Delmenhorst
    Delmenhorst is a mid-sized industrial and commuter city in northwestern Germany, located near Bremen in the federal state of Lower Saxony.
  • 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_69ca83a5fa88819088144801b4dd7245 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6a7ce71c81908041814dc9ec1713 completed April 1, 2026, 12:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfdbbf786081908df45b4e615bbba9 completed April 3, 2026, 3:24 p.m.
Created at: March 30, 2026, 7:07 p.m.