Triple

T18478229
Position Surface form Disambiguated ID Type / Status
Subject Rolandswerth E451487 entity
Predicate hasLandmark P105 FINISHED
Object Rolandseck station 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: Rolandseck station | Statement: [Rolandswerth, hasLandmark, Rolandseck station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rolandseck station
Context triple: [Rolandswerth, hasLandmark, Rolandseck station]
  • A. Rolandseck railway station chosen
    Rolandseck railway station is a historic train station on the Rhine in Remagen, Germany, known for its 19th-century architecture and its integration with the Arp Museum as a cultural venue.
  • B. Langenau station
    Langenau station is a regional railway stop in the town of Langenau in Baden-Württemberg, Germany, serving local passenger rail services.
  • C. Meckesheim station
    Meckesheim station is a regional railway stop in the town of Meckesheim in Baden-Württemberg, Germany, serving local passenger services on surrounding rail lines.
  • D. Trier Süd station
    Trier Süd station is a secondary railway station in the city of Trier, Germany, serving regional passenger traffic south of the main Trier Hauptbahnhof.
  • E. Kuppenheim station
    Kuppenheim station is a local railway stop in the town of Kuppenheim in Baden-Württemberg, Germany, serving regional passenger traffic.
  • 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_69d8d38465a0819099b9b42d2a662ac1 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e53064a7548190b712a14ad0c7a477 completed April 19, 2026, 7:43 p.m.
Created at: April 10, 2026, 11:35 a.m.