Triple

T9767113
Position Surface form Disambiguated ID Type / Status
Subject Rudolfswerth E237020 entity
Predicate replacedByName P3432 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: [Rudolfswerth, replacedByName, Novo Mesto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Novo Mesto
Context triple: [Rudolfswerth, replacedByName, 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_69ca84d831b8819090322686b47887ce completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda0a15e408190909745cb1c30937d completed April 1, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1e4064c8c8190b18f419135f049a9 completed April 5, 2026, 4:24 a.m.
Created at: March 30, 2026, 8:25 p.m.