Triple

T8811579
Position Surface form Disambiguated ID Type / Status
Subject Švenčionys E209675 entity
Predicate locatedNear P294 FINISHED
Object Švenčionėliai E209675 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: Švenčionėliai | Statement: [Švenčionys, locatedNear, Švenčionėliai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Švenčionėliai
Context triple: [Švenčionys, locatedNear, Švenčionėliai]
  • A. Švenčionys chosen
    Švenčionys is a small historic town in eastern Lithuania known for its multicultural past and former Jewish community.
  • B. Mažeikiai
    Mažeikiai is a town in northwestern Lithuania known for its large oil refinery and role as an industrial and transport hub in the Samogitia region.
  • C. Kėdainiai
    Kėdainiai is a historic city in central Lithuania known for its well-preserved old town and multicultural heritage.
  • D. Varniai
    Varniai is a historic town in Lithuania that once served as a key political and religious center of the Samogitian region.
  • E. Elektrėnai
    Elektrėnai is a Lithuanian town best known for its major thermal power plant and artificial reservoir, which have made it an important energy and recreational center in the country.
  • 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_69ca8363f3308190a47e3f1ebd51f613 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5fed18f8819087b0282bf8c4208c completed March 31, 2026, 11:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf6fb26b148190b66b7138cdf9c97b completed April 3, 2026, 7:43 a.m.
Created at: March 30, 2026, 6:45 p.m.