Triple

T8056239
Position Surface form Disambiguated ID Type / Status
Subject Revoz E188008 entity
Predicate city P40 FINISHED
Object Novo Mesto E36037 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: Novo Mesto | Statement: [Revoz, city, Novo Mesto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Novo Mesto
Context triple: [Revoz, city, Novo Mesto]
  • A. Kranj
    Kranj is a historic industrial city in northwestern Slovenia, known as a regional economic center and gateway to the Slovenian Alps.
  • B. 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.
  • C. Sevnica
    Sevnica is a small town in central Slovenia known as the childhood home of former U.S. First Lady Melania Trump.
  • D. Maribor
    Maribor is Slovenia’s second-largest city, known for its historic old town, wine culture, and the world’s oldest grapevine.
  • E. Novo Mesto, Slovenia chosen
    Novo Mesto is a historic town in southeastern Slovenia known for its cultural heritage and picturesque setting on the Krka River.
  • 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_69ca82b2f68881908c50560697e210da completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3fa26fb88190b6799bddeb68ed78 completed March 31, 2026, 3:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69cea7d3587881909539a7bea05e328a completed April 2, 2026, 5:30 p.m.
Created at: March 30, 2026, 5:25 p.m.