Triple

T16886571
Position Surface form Disambiguated ID Type / Status
Subject Šiauliai County E421554 entity
Predicate hasRailwayJunction P918 FINISHED
Object Radviliškis E1251875 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: Radviliškis | Statement: [Šiauliai County, hasRailwayJunction, Radviliškis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Radviliškis
Context triple: [Šiauliai County, hasRailwayJunction, Radviliškis]
  • A. Radviliškis chosen
    Radviliškis is a town in northern Lithuania known as a regional railway hub and administrative center within Šiauliai County.
  • B. Vilkaviškis
    Vilkaviškis is a town in southwestern Lithuania known as an administrative and historical center of the surrounding agricultural region.
  • C. Zarasai
    Zarasai is a small town in northeastern Lithuania known for its lakes and scenic natural surroundings.
  • D. Joniškis
    Joniškis is a small town in northern Lithuania known for its historic architecture and cultural heritage, including well-preserved synagogues.
  • E. Rokiškis
    Rokiškis is a town in northeastern Lithuania known for its well-preserved manor, historic architecture, and role as a regional cultural center.
  • 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_69d889d470fc8190b4aec199636c0c56 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3bbc126e881909dae8133ad34acc9 completed April 18, 2026, 5:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a017932fd5481909bf3c63409fd6da6 completed May 11, 2026, 6:37 a.m.
Created at: April 10, 2026, 5:29 a.m.