Triple

T7670131
Position Surface form Disambiguated ID Type / Status
Subject Tivoli Park E173725 entity
Predicate operator P179 FINISHED
Object City of Ljubljana E32117 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: City of Ljubljana | Statement: [Tivoli Park, operator, City of Ljubljana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Ljubljana
Context triple: [Tivoli Park, operator, City of Ljubljana]
  • A. Ljubljana chosen
    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.
  • B. Maribor
    Maribor is Slovenia’s second-largest city, known for its historic old town, wine culture, and the world’s oldest grapevine.
  • C. Celje
    Celje is a historic city in eastern Slovenia known for its medieval castle and former prominence as a regional political and economic center.
  • D. Novo Mesto, Slovenia
    Novo Mesto is a historic town in southeastern Slovenia known for its cultural heritage and picturesque setting on the Krka River.
  • 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_69c699562484819086752091e3164a27 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c701c5538881908139881daf41151a completed March 27, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c95ffa6a3c819089aa939b164dbcaa completed March 29, 2026, 5:23 p.m.
Created at: March 27, 2026, 4 p.m.