Triple

T17112173
Position Surface form Disambiguated ID Type / Status
Subject KTU E415251 entity
Predicate campusLocation P269 FINISHED
Object Kaunas, Lithuania 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: Kaunas, Lithuania | Statement: [KTU, campusLocation, Kaunas, Lithuania]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kaunas, Lithuania
Context triple: [KTU, campusLocation, Kaunas, Lithuania]
  • A. Kaunas chosen
    Kaunas is the second-largest city in Lithuania, known as a historic cultural and academic center located at the confluence of the Nemunas and Neris rivers.
  • B. Kaunas metropolitan area
    The Kaunas metropolitan area is an urban agglomeration in central Lithuania centered on the city of Kaunas, encompassing its surrounding municipalities and suburbs as a major economic and cultural hub.
  • C. Joniškis
    Joniškis is a small town in northern Lithuania known for its historic architecture and cultural heritage, including well-preserved synagogues.
  • D. Vilnius
    Vilnius is the capital and largest city of Lithuania, known for its well-preserved medieval Old Town and rich cultural and historical heritage.
  • E. Klaipėda
    Klaipėda is a Lithuanian port city on the Baltic Sea known as the country’s main maritime gateway and a key regional transport and industrial hub.
  • 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.