Triple

T9498586
Position Surface form Disambiguated ID Type / Status
Subject Weiden in der Oberpfalz E229075 entity
Predicate hasTwinTown P919 FINISHED
Object Maribor E114358 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: Maribor | Statement: [Weiden in der Oberpfalz, hasTwinTown, Maribor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maribor
Context triple: [Weiden in der Oberpfalz, hasTwinTown, Maribor]
  • A. Maribor chosen
    Maribor is Slovenia’s second-largest city, known for its historic old town, wine culture, and the world’s oldest grapevine.
  • B. Celje
    Celje is a historic city in eastern Slovenia known for its medieval castle and former prominence as a regional political and economic center.
  • C. Ljubljana
    Ljubljana is the capital and largest city of Slovenia, known for its picturesque old town, Baroque and Art Nouveau architecture, and vibrant cultural scene along the Ljubljanica River.
  • D. Kranj
    Kranj is a historic industrial city in northwestern Slovenia, known as a regional economic center and gateway to the Slovenian Alps.
  • E. Velenje
    Velenje is a modern industrial town in northern Slovenia known for its coal mining heritage, large lakeside recreational area, and one of the largest Tito statues in the world.
  • 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_69ca84753660819098e8d416e89e26ae completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd95ef06b88190b7a840caddea3e38 completed April 1, 2026, 10:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69d12d3aafb88190ac53289039bca88a completed April 4, 2026, 3:24 p.m.
Created at: March 30, 2026, 7:56 p.m.