Triple

T10658337
Position Surface form Disambiguated ID Type / Status
Subject Kaiser Wilhelm Bridge E251154 entity
Predicate locatedIn P40 FINISHED
Object Wilhelmshaven 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 | Statement: [Kaiser Wilhelm Bridge, locatedIn, Wilhelmshaven]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wilhelmshaven
Context triple: [Kaiser Wilhelm Bridge, locatedIn, Wilhelmshaven]
  • A. Wilhelmshaven chosen
    Wilhelmshaven is a coastal city in northwestern Germany known for its major naval base and port on the North Sea.
  • B. Cuxhaven
    Cuxhaven is a German port city on the North Sea coast that historically served as an important naval and maritime hub.
  • C. Dover
    Dover is a residential and educational neighborhood in western Singapore, known for its proximity to universities and polytechnics.
  • D. Dover
    Dover is a small town in eastern Dutchess County, New York, known for its rural character and location near the Connecticut border.
  • E. Dover
    Dover is one of the oldest permanent European settlements in what is now the U.S. state of New Hampshire, historically significant as an early colonial town and port.
  • 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_69d6aa5a4c4881908f39be6efe5981e5 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6e01643a88190abc7c16fd0f85e53 completed April 8, 2026, 11:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69d97a8375bc8190a79c09ba2626ce50 completed April 10, 2026, 10:32 p.m.
Created at: April 8, 2026, 9:07 p.m.