Triple

T22277731
Position Surface form Disambiguated ID Type / Status
Subject Tichá Orlice E550649 entity
Predicate flowsThrough P225 FINISHED
Object Letohrad NE NERFINISHED

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: Letohrad | Statement: [Tichá Orlice, flowsThrough, Letohrad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Letohrad
Context triple: [Tichá Orlice, flowsThrough, Letohrad]
  • A. Letohrad chosen
    Letohrad is a small town in the Pardubice Region of the Czech Republic, known for its historic center and location in the Orlické Mountains foothills.
  • B. Strakonice
    Strakonice is a historic town in the Czech Republic known for its medieval castle and traditional bagpipe festival.
  • C. Uherské Hradiště
    Uherské Hradiště is a historic town in the Zlín Region of the Czech Republic, known as a cultural center of the Moravian Slovakia ethnographic area.
  • D. Rajhrad
    Rajhrad is a historic town in the South Moravian Region of the Czech Republic, known for its Benedictine monastery and proximity to the city of Brno.
  • E. Osek
    Osek is a town in the Czech Republic historically associated with the family origins of writer Franz Kafka’s father, Hermann Kafka.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e44d538819097c6b8f333af3352 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f14ea96948819081c1ae6c7b11ab62 completed April 29, 2026, 12:19 a.m.
Created at: April 16, 2026, 8:40 p.m.