Triple

T5371157
Position Surface form Disambiguated ID Type / Status
Subject Vltava River E108852 entity
Predicate flowsThrough P225 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: [Vltava River, flowsThrough, České Budějovice]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: České Budějovice
Context triple: [Vltava River, flowsThrough, 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. Žatec
    Žatec is a historic Czech town in the Ústí nad Labem Region renowned for its long-standing hop-growing tradition and beer production.
  • C. Plzeň
    Plzeň is a major city in western Bohemia in the Czech Republic, known for its brewing tradition and industrial heritage.
  • D. Jihlava
    Jihlava is a river in the Czech Republic that flows through the historical region of Moravia, including the city of Jihlava, before joining the Svratka River.
  • E. 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.
  • 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_69bd440c77948190aad2a5f39b7b80f5 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd8688b7488190a57baedd52a11b1a completed March 20, 2026, 5:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69c059bd73e481909e23e1796262b8c4 completed March 22, 2026, 9:06 p.m.
Created at: March 20, 2026, 2:02 p.m.