Triple

T4937251
Position Surface form Disambiguated ID Type / Status
Subject Radbuza E110841 entity
Predicate flowsThrough P225 FINISHED
Object Holýšov E304852 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: Holýšov | Statement: [Radbuza, flowsThrough, Holýšov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Holýšov
Context triple: [Radbuza, flowsThrough, Holýšov]
  • A. Holýšov chosen
    Holýšov is a town in the Czech Republic known for its industrial history and location in the western Plzeň Region.
  • B. Pohořelice
    Pohořelice is a small town in the South Moravian Region of the Czech Republic, known for its agricultural surroundings and proximity to the city of Brno.
  • C. Hořovice
    Hořovice is a small Czech town known for its historic chateau and location in the western part of the Central Bohemian Region.
  • D. Hořice
    Hořice is a small Czech town known for its sandstone sculptures and traditional Hořice rolled wafers, located in the Hradec Králové Region.
  • E. Trebišov
    Trebišov is a town in eastern Slovakia known as an administrative and cultural center of the Trebišov District.
  • 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_69be923eac848190b8511b8027c87ff3 completed March 21, 2026, 12:42 p.m.
Created at: March 20, 2026, 1:31 p.m.