Triple

T4937241
Position Surface form Disambiguated ID Type / Status
Subject Radbuza E110841 entity
Predicate riverMouth P4359 FINISHED
Object Berounka E289129 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: Berounka | Statement: [Radbuza, riverMouth, Berounka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Berounka
Context triple: [Radbuza, riverMouth, Berounka]
  • A. Berounka chosen
    Berounka is a major river in western Bohemia in the Czech Republic, known for flowing through the Plzeň Region and eventually joining the Vltava near Prague.
  • B. Svitava
    Svitava is a river in the Czech Republic that flows through the city of Brno and is one of its main waterways.
  • C. Blšanka
    Blšanka is a small river in the Czech Republic that flows through the Ústí nad Labem and Karlovy Vary regions before joining the Ohře River.
  • D. Lučina
    Lučina is a river in the Moravian-Silesian Region of the Czech Republic that flows through the city of Ostrava.
  • E. Brda
    Brda is a river in northern Poland that flows through the Pomeranian region and is known for its scenic landscapes and popular kayaking routes.
  • 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_69bd4415eee08190bdce70276e56a5b4 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd70872270819080769dad972681ef completed March 20, 2026, 4:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69beba512f1881909e9bf062fe416ac8 completed March 21, 2026, 3:33 p.m.
Created at: March 20, 2026, 1:31 p.m.