Triple

T17112333
Position Surface form Disambiguated ID Type / Status
Subject Lithuanian airport network E415255 entity
Predicate regionalAirport P17216 FINISHED
Object Palanga Airport 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: Palanga Airport | Statement: [Lithuanian airport network, regionalAirport, Palanga Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Palanga Airport
Context triple: [Lithuanian airport network, regionalAirport, Palanga Airport]
  • A. Palanga Airport chosen
    Palanga Airport is a regional international airport in western Lithuania serving the coastal resort city of Palanga and the surrounding Baltic Sea region.
  • B. Vilnius Airport
    Vilnius Airport is the main international airport serving Lithuania’s capital, handling the majority of the region’s passenger and air traffic.
  • C. Kaunas Airport
    Kaunas Airport is an international airport in Lithuania serving the city of Kaunas and functioning as one of the country’s main commercial and low-cost airline hubs.
  • D. Ventspils International Airport
    Ventspils International Airport is a regional airport in Ventspils, Latvia, serving as an air transport hub for the city and surrounding Kurzeme region.
  • E. Viedma Airport
    Viedma Airport is a regional public airport serving the city of Viedma and surrounding areas in Argentina’s Río Negro Province.
  • 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_69d886d090cc8190a39cb94992586905 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dc2bab0881908339ec7fb3ebe7e9 completed April 18, 2026, 7:31 p.m.
Created at: April 10, 2026, 5:35 a.m.