Triple

T17143117
Position Surface form Disambiguated ID Type / Status
Subject Louny E416018 entity
Predicate hasNearbyCity P350 FINISHED
Object Rakovník E181631 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: Rakovník | Statement: [Louny, hasNearbyCity, Rakovník]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rakovník
Context triple: [Louny, hasNearbyCity, Rakovník]
  • A. Rakovník chosen
    Rakovník is a historic town in the Czech Republic known for its traditional architecture, brewing heritage, and role as a local administrative and cultural center.
  • B. Račak
    Račak is a village in Kosovo best known internationally as the site of the 1999 Račak massacre, a pivotal event in the Kosovo conflict.
  • C. Rakovica
    Rakovica is a village and municipality in central Croatia known for its natural surroundings and proximity to the Plitvice Lakes area.
  • D. Rakovica
    Rakovica is a suburban municipality of Belgrade, Serbia, known for its mixed residential and industrial areas and proximity to forested landscapes.
  • E. Ráckeve
    Ráckeve is a historic town in central Hungary situated along the Danube River, known for its Serbian cultural heritage and baroque architecture.
  • 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_69d886d15af4819092f92f8a129763e6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3f2d73c3c81908b875023bb925edb completed April 18, 2026, 9:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a01415718c88190834fedae7b01ac69 completed May 11, 2026, 2:39 a.m.
Created at: April 10, 2026, 5:36 a.m.