Triple

T3822986
Position Surface form Disambiguated ID Type / Status
Subject Sezimovo Ústí E88618 entity
Predicate hasNearbyCity P350 FINISHED
Object České Budějovice E186483 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: České Budějovice | Statement: [Sezimovo Ústí, hasNearbyCity, České Budějovice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: České Budějovice
Context triple: [Sezimovo Ústí, hasNearbyCity, České Budějovice]
  • A. České Budějovice chosen
    České Budějovice is a historic city in the Czech Republic known for its medieval architecture and as the original home of Budweiser Budvar beer.
  • B. Plzeň
    Plzeň is a major city in western Bohemia in the Czech Republic, known for its brewing tradition and industrial heritage.
  • C. Jihlava
    Jihlava is a historic city in the Czech Republic, known as one of the country’s oldest mining towns and a regional cultural and administrative center.
  • D. Liberec
    Liberec is a city in the northern Czech Republic known for its textile industry heritage, mountainous surroundings, and the landmark Ještěd Tower.
  • E. Kolín
    Kolín is a historic industrial town and important transport hub on the Elbe River in the Central Bohemian Region of the Czech Republic.
  • 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_69aed9538cf881909d9ce8ca4ac7c18c completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aeea63fe2c8190825f6e9451f6aa50 completed March 9, 2026, 3:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69b51222e5b08190aa4ac79722219798 completed March 14, 2026, 7:45 a.m.
Created at: March 9, 2026, 3:17 p.m.