Triple

T4700556
Position Surface form Disambiguated ID Type / Status
Subject Krk E104257 entity
Predicate hasAirport P105 FINISHED
Object Rijeka Airport E313768 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: Rijeka Airport | Statement: [Krk, hasAirport, Rijeka Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rijeka Airport
Context triple: [Krk, hasAirport, Rijeka Airport]
  • A. Rijeka Airport chosen
    Rijeka Airport is an international airport serving the city of Rijeka and the surrounding Kvarner region on the Croatian island of Krk.
  • B. Zadar Airport
    Zadar Airport is an international airport in Croatia serving the city of Zadar and the surrounding Dalmatian coast, handling both commercial and seasonal tourist flights.
  • C. Lošinj Airport
    Lošinj Airport is a small regional airport serving the island of Lošinj and surrounding areas on Croatia’s northern Adriatic coast.
  • D. Dubrovnik Airport
    Dubrovnik Airport is an international airport serving the coastal city of Dubrovnik in southern Croatia and is one of the country’s key gateways for tourism and air travel.
  • E. Zagreb Franjo Tuđman Airport
    Zagreb Franjo Tuđman Airport is the main international airport serving Croatia’s capital city, functioning as the country’s busiest air transport hub.
  • 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_69bd43e9b88481908582103dcadff3d9 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd63cd447081908120ee1691009982 completed March 20, 2026, 3:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69be03ca24848190aa7df32472647cae completed March 21, 2026, 2:34 a.m.
Created at: March 20, 2026, 1:17 p.m.