Triple

T8862088
Position Surface form Disambiguated ID Type / Status
Subject North Moravia E210913 entity
Predicate hasTransportHub P2413 FINISHED
Object Ostrava Airport E172961 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: Ostrava Airport | Statement: [North Moravia, hasTransportHub, Ostrava Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ostrava Airport
Context triple: [North Moravia, hasTransportHub, Ostrava Airport]
  • A. Leoš Janáček Airport Ostrava chosen
    Leoš Janáček Airport Ostrava is an international airport in the Czech Republic serving the city of Ostrava and the surrounding Moravian-Silesian region.
  • B. Olomouc Airport
    Olomouc Airport is a regional airfield serving the city of Olomouc in the Czech Republic, primarily used for general aviation and smaller aircraft operations.
  • C. Pardubice Airport
    Pardubice Airport is a regional international airport in the Czech Republic that serves both civilian and military air traffic.
  • D. Brno–Tuřany Airport
    Brno–Tuřany Airport is an international airport serving the city of Brno in the South Moravian Region of the Czech Republic.
  • E. Hradec Králové Airport
    Hradec Králové Airport is a regional civil and general aviation airport serving the city of Hradec Králové in the Czech Republic.
  • 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_69ca838bbddc8190ab546d737e5d350f completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc610263048190931bb2c3ac573a08 completed April 1, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfa0c248108190815d593f44029183 completed April 3, 2026, 11:13 a.m.
Created at: March 30, 2026, 6:50 p.m.