Triple

T1667150
Position Surface form Disambiguated ID Type / Status
Subject Novo Mesto E36037 entity
Predicate hasMunicipalSeat P1474 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: [Novo Mesto, hasMunicipalSeat, Novo Mesto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Novo Mesto
Context triple: [Novo Mesto, hasMunicipalSeat, Novo Mesto]
  • A. Maribor
    Maribor is Slovenia’s second-largest city, known for its historic old town, wine culture, and the world’s oldest grapevine.
  • B. 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.
  • C. Kladno
    Kladno is an industrial city in the Czech Republic known historically for coal mining and steel production.
  • D. Gospić
    Gospić is a town in the Lika region of Croatia, known as the administrative center of Lika-Senj County and for its association with the birthplace of inventor Nikola Tesla in nearby Smiljan.
  • E. Ptuj
    Ptuj is one of Slovenia’s oldest towns, renowned for its well-preserved medieval architecture and rich cultural heritage along the Drava 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_69a8861286808190939afff3ce8ee31e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a90adc57cc8190b270004c363768e3 completed March 5, 2026, 4:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad683207b08190a86c266aaece4e98 completed March 8, 2026, 12:14 p.m.
Created at: March 4, 2026, 7:29 p.m.