Triple

T16913831
Position Surface form Disambiguated ID Type / Status
Subject LKPR E410270 entity
Predicate formerName P65 FINISHED
Object Ruzyně Airport E1242973 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: Ruzyně Airport | Statement: [LKPR, formerName, Ruzyně Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ruzyně Airport
Context triple: [LKPR, formerName, Ruzyně Airport]
  • A. Ruzyně Airport chosen
    Ruzyně Airport is the former name of Prague's main international airport, now known as Václav Havel Airport Prague, serving as the primary air gateway to the Czech Republic.
  • B. Pardubice Airport
    Pardubice Airport is a regional international airport in the Czech Republic that serves both civilian and military air traffic.
  • C. Brno–Tuřany Airport
    Brno–Tuřany Airport is an international airport serving the city of Brno in the South Moravian Region of the Czech Republic.
  • D. 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.
  • E. Karlovy Vary Airport
    Karlovy Vary Airport is a regional international airport in the Czech Republic serving the spa city of Karlovy Vary and its surrounding area.
  • 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_69d886c7b1e481908c3766dfa8c13458 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3ca3f1a2c8190a512ccc09a080eb4 completed April 18, 2026, 6:15 p.m.
NED1 Entity disambiguation (via context triple) batch_6a012ecafd908190b8a1513138a29303 completed May 11, 2026, 1:20 a.m.
Created at: April 10, 2026, 5:30 a.m.