Triple

T17847221
Position Surface form Disambiguated ID Type / Status
Subject Varniai E445695 entity
Predicate hasNearbyCity P350 FINISHED
Object Telšiai 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: Telšiai | Statement: [Varniai, hasNearbyCity, Telšiai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Telšiai
Context triple: [Varniai, hasNearbyCity, Telšiai]
  • A. Telšiai chosen
    Telšiai is a historic city in northwestern Lithuania that serves as the cultural and administrative center of the Samogitia region.
  • B. Tauragė
    Tauragė is a town in western Lithuania known as an administrative, cultural, and economic center of the surrounding region.
  • C. Radviliškis
    Radviliškis is a town in northern Lithuania known as a regional railway hub and administrative center within Šiauliai County.
  • D. Vilkaviškis
    Vilkaviškis is a town in southwestern Lithuania known as an administrative and historical center of the surrounding agricultural region.
  • E. Joniškis
    Joniškis is a small town in northern Lithuania known for its historic architecture and cultural heritage, including well-preserved synagogues.
  • 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_69d8b9f26f18819089c9e43250bee6ae completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48ffb35248190a80a428686e06d87 completed April 19, 2026, 8:19 a.m.
Created at: April 10, 2026, 10:16 a.m.