Triple

T17847222
Position Surface form Disambiguated ID Type / Status
Subject Varniai E445695 entity
Predicate hasNearbyCity P350 FINISHED
Object Šiauliai 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: Šiauliai | Statement: [Varniai, hasNearbyCity, Šiauliai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Šiauliai
Context triple: [Varniai, hasNearbyCity, Šiauliai]
  • A. Šiauliai chosen
    Šiauliai is one of the largest cities in Lithuania, known as a regional industrial and cultural center in the northern part of the country.
  • B. Tauragė
    Tauragė is a town in western Lithuania known as an administrative, cultural, and economic center of the surrounding region.
  • C. 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.
  • D. Radviliškis
    Radviliškis is a town in northern Lithuania known as a regional railway hub and administrative center within Šiauliai County.
  • E. Zarasai
    Zarasai is a small town in northeastern Lithuania known for its lakes and scenic natural surroundings.
  • 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.