Triple

T4144467
Position Surface form Disambiguated ID Type / Status
Subject Kaunas Airport E89349 entity
Predicate locatedIn P40 FINISHED
Object Kaunas County E87721 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: Kaunas County | Statement: [Kaunas Airport, locatedIn, Kaunas County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kaunas County
Context triple: [Kaunas Airport, locatedIn, Kaunas County]
  • A. Kaunas County chosen
    Kaunas County is an administrative region in central Lithuania that encompasses the country’s second-largest city, Kaunas, and serves as an important economic and cultural hub.
  • B. Marijampolė County
    Marijampolė County is an administrative region in southern Lithuania known for its agricultural landscape and the city of Marijampolė as its capital.
  • C. Tauragė County
    Tauragė County is an administrative region in western Lithuania known for its small industrial centers and proximity to the border with Kaliningrad Oblast (Russia).
  • D. Šiauliai County
    Šiauliai County is one of the administrative counties of northern Lithuania, centered on the city of Šiauliai and known for its industrial base and cultural heritage.
  • E. Alytus County
    Alytus County is an administrative region in southern Lithuania known for its forests, lakes, and the city of Alytus as its main urban center.
  • 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_69aed95785788190ae75bcf0cd1cafdf completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af025e850c819085ec05b9d9b60712 completed March 9, 2026, 5:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69b627befdd881908b602fd80f030405 completed March 15, 2026, 3:30 a.m.
Created at: March 9, 2026, 3:43 p.m.