Triple

T20787971
Position Surface form Disambiguated ID Type / Status
Subject Ernst-Moritz-Arndt-Turm E511690 entity
Predicate hasViewOf P854 FINISHED
Object central Rügen 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: central Rügen | Statement: [Ernst-Moritz-Arndt-Turm, hasViewOf, central Rügen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: central Rügen
Context triple: [Ernst-Moritz-Arndt-Turm, hasViewOf, central Rügen]
  • A. Rügen
    Rügen is Germany’s largest island, known for its chalk cliffs, seaside resorts, and beaches along the Baltic Sea coast.
  • B. Hiddensee
    Hiddensee is a car-free German Baltic Sea island known for its unspoiled nature, sandy beaches, and role as a tranquil holiday destination west of Rügen.
  • C. Hiddensee
    Hiddensee is a novel by Gregory Maguire that reimagines the backstory of the Nutcracker and its mysterious creator in a dark, folkloric fantasy.
  • D. Bergen auf Rügen chosen
    Bergen auf Rügen is the central town and administrative hub of Germany’s Baltic Sea island of Rügen, known for its historic old town and proximity to the island’s coastal attractions.
  • E. Rostock-Land
    Rostock-Land was a rural district in the former East German administrative region centered around the city of Rostock.
  • 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_69e0b4cb83948190bd57bec21d78ed53 completed April 16, 2026, 10:07 a.m.
NER Named-entity recognition batch_69e6c28d24708190bf3890a22d1ec4b7 completed April 21, 2026, 12:19 a.m.
Created at: April 16, 2026, 12:38 p.m.