Triple

T22743856
Position Surface form Disambiguated ID Type / Status
Subject Šarūnas Marčiulionis E562490 entity
Predicate residence P75 FINISHED
Object Vilnius, 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: Vilnius, Lithuania | Statement: [Šarūnas Marčiulionis, residence, Vilnius, Lithuania]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vilnius, Lithuania
Context triple: [Šarūnas Marčiulionis, residence, Vilnius, Lithuania]
  • A. Vilnius chosen
    Vilnius is the capital and largest city of Lithuania, known for its well-preserved medieval Old Town and rich cultural and historical heritage.
  • B. Kaunas
    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.
  • C. Zarasai
    Zarasai is a small town in northeastern Lithuania known for its lakes and scenic natural surroundings.
  • D. Vilkaviškis
    Vilkaviškis is a town in southwestern Lithuania known as an administrative and historical center of the surrounding agricultural region.
  • E. Statyba Vilnius
    Statyba Vilnius was a prominent basketball club from Vilnius, Lithuania, known for competing in the Soviet and later Lithuanian basketball leagues.
  • 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_69e245513a5c81908d5cb471b4fc429d completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1797590f08190a784f73fcd27b101 completed April 29, 2026, 3:22 a.m.
Created at: April 17, 2026, 3:23 p.m.