Triple

T11795989
Position Surface form Disambiguated ID Type / Status
Subject Nitra Region E280506 entity
Predicate hasCity P316 FINISHED
Object Kolárovo E278187 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: Kolárovo | Statement: [Nitra Region, hasCity, Kolárovo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kolárovo
Context triple: [Nitra Region, hasCity, Kolárovo]
  • A. Kolárovo chosen
    Kolárovo is a small town in southern Slovakia known for its multicultural Hungarian-Slovak character and historic wooden bridge over the Little Danube.
  • B. Kapesovo
    Kapesovo is a traditional stone-built village in the Zagori region of Epirus, Greece, known for its preserved architecture and scenic mountainous setting.
  • C. Karmanovo
    Karmanovo is a rural village located within the Gagarinsky District of Smolensk Oblast in western Russia.
  • D. Lozova
    Lozova is a town in eastern Ukraine that has historically been a strategic railway and military junction.
  • E. Karlovo
    Karlovo is a historic town in central Bulgaria, known as the birthplace of national hero Vasil Levski and as a gateway to the Balkan Mountains.
  • 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_69d6ab258b808190b1735835c841e3a4 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a5a1cda0819092d66a82fd882786 completed April 10, 2026, 7:24 a.m.
NED1 Entity disambiguation (via context triple) batch_69f130fd7b9881909e79ecb49fe98d30 completed April 28, 2026, 10:13 p.m.
Created at: April 8, 2026, 9:42 p.m.