Triple

T4937250
Position Surface form Disambiguated ID Type / Status
Subject Radbuza E110841 entity
Predicate flowsThrough P225 FINISHED
Object Staňkov
Staňkov is a small town in the Plzeň Region of the Czech Republic, known for its location on the Radbuza River and its traditional West Bohemian character.
 E481676 NE FINISHED

How this triple was built (4 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: Staňkov | Statement: [Radbuza, flowsThrough, Staňkov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Staňkov
Context triple: [Radbuza, flowsThrough, Staňkov]
  • A. Štrkovec
    Štrkovec is a residential neighborhood and cadastral area within the Ružinov borough of Bratislava, Slovakia.
  • B. Štúrovo
    Štúrovo is a Slovak town on the Danube River opposite Esztergom, Hungary, known for its cross-border bridge and thermal spa tourism.
  • C. Vávrová
    Vávrová is a Czech surname most notably borne by Dana Vávrová, a well-known Czech-German actress and film director.
  • D. Svatava
    Svatava is a river in Central Europe that flows through parts of Germany and the Czech Republic before joining the Ohře River.
  • E. Kopřivnice
    Kopřivnice is a town in the Moravian-Silesian Region of the Czech Republic, known for its automotive industry and as the birthplace of legendary long-distance runner Emil Zátopek.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Staňkov
Triple: [Radbuza, flowsThrough, Staňkov]
Generated description
Staňkov is a small town in the Plzeň Region of the Czech Republic, known for its location on the Radbuza River and its traditional West Bohemian character.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Staňkov
Target entity description: Staňkov is a small town in the Plzeň Region of the Czech Republic, known for its location on the Radbuza River and its traditional West Bohemian character.
  • A. Štrkovec
    Štrkovec is a residential neighborhood and cadastral area within the Ružinov borough of Bratislava, Slovakia.
  • B. Štúrovo
    Štúrovo is a Slovak town on the Danube River opposite Esztergom, Hungary, known for its cross-border bridge and thermal spa tourism.
  • C. Vávrová
    Vávrová is a Czech surname most notably borne by Dana Vávrová, a well-known Czech-German actress and film director.
  • D. Svatava
    Svatava is a river in Central Europe that flows through parts of Germany and the Czech Republic before joining the Ohře River.
  • E. Kopřivnice
    Kopřivnice is a town in the Moravian-Silesian Region of the Czech Republic, known for its automotive industry and as the birthplace of legendary long-distance runner Emil Zátopek.
  • F. None of above. chosen

Provenance (5 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_69be77bcb8d881908d393223bdea145a completed March 21, 2026, 10:49 a.m.
NEDg Description generation batch_69be78747f3881908afe9cf276216bc5 completed March 21, 2026, 10:52 a.m.
NED2 Entity disambiguation (via description) batch_69be78d03aec81909a2470306ba90cb0 completed March 21, 2026, 10:54 a.m.
Created at: March 20, 2026, 1:31 p.m.