Triple

T19033652
Position Surface form Disambiguated ID Type / Status
Subject Vilnius County E465807 entity
Predicate hasCity P316 FINISHED
Object Elektrėnai 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: Elektrėnai | Statement: [Vilnius County, hasCity, Elektrėnai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elektrėnai
Context triple: [Vilnius County, hasCity, Elektrėnai]
  • A. Elektrėnai chosen
    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.
  • B. Švenčionys
    Švenčionys is a small historic town in eastern Lithuania known for its multicultural past and former Jewish community.
  • C. Radviliškis
    Radviliškis is a town in northern Lithuania known as a regional railway hub and administrative center within Šiauliai County.
  • D. Joniškis
    Joniškis is a small town in northern Lithuania known for its historic architecture and cultural heritage, including well-preserved synagogues.
  • E. Šilutė
    Šilutė is a town in western Lithuania known for its location near the Nemunas River delta and its historical ties to the former East Prussian region.
  • 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_69d8dd0359648190bc2a9202c5cf29d2 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d741cabc8190900e12265ad269f8 completed April 20, 2026, 7:35 a.m.
Created at: April 10, 2026, 12:02 p.m.