Triple

T11688571
Position Surface form Disambiguated ID Type / Status
Subject Peenebrücke Wolgast E277806 entity
Predicate serves P98 FINISHED
Object town of Wolgast E529361 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: town of Wolgast | Statement: [Peenebrücke Wolgast, serves, town of Wolgast]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: town of Wolgast
Context triple: [Peenebrücke Wolgast, serves, town of Wolgast]
  • A. Wolgast chosen
    Wolgast is a small town in northeastern Germany on the Baltic Sea coast, historically significant as a port and former naval base.
  • B. Town of Schleswig
    The Town of Schleswig is a small rural municipality in eastern Wisconsin known for its agricultural landscape and quiet residential character within Manitowoc County.
  • C. Wierzbnik town
    Wierzbnik was a former town in Poland that later became part of the modern city of Starachowice through an administrative merger.
  • D. Wustrow
    Wustrow is a small town in the Wendland region of Lower Saxony, Germany, known for its rural character and traditional half-timbered architecture.
  • E. town of Tangermünde
    The town of Tangermünde is a historic German town on the Elbe River, renowned for its well-preserved medieval architecture and brick Gothic buildings.
  • 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_69d6aafe02d881909900d54ad7d4af84 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a478f4c481908b2ba7b70972590d completed April 10, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef831d27248190894ffdb12c1ddd4d completed April 27, 2026, 3:39 p.m.
Created at: April 8, 2026, 9:40 p.m.