Triple

T5270887
Position Surface form Disambiguated ID Type / Status
Subject Imatra E119253 entity
Predicate adjacentTo P224 FINISHED
Object Svetogorsk E316280 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: Svetogorsk | Statement: [Imatra, adjacentTo, Svetogorsk]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Svetogorsk
Context triple: [Imatra, adjacentTo, Svetogorsk]
  • A. Svetogorsk chosen
    Svetogorsk is a small industrial town in northwestern Russia near the Finnish border, known for its paper mill and location along the Vuoksi River.
  • B. Svetlogorsk
    Svetlogorsk is a coastal resort town on the Baltic Sea in Russia’s Kaliningrad Oblast, known for its beaches, sanatoriums, and picturesque seaside promenade.
  • C. Malinska
    Malinska is a coastal resort town and popular tourist destination on the island of Krk in Croatia, known for its beaches and Mediterranean atmosphere.
  • D. Plavsk
    Plavsk is a small town in western Russia known for its agricultural surroundings and location within the Tula region.
  • E. Primorsk
    Primorsk is a port town in northwestern Russia situated on the coast of the Gulf of Finland in Leningrad Oblast.
  • 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_69bd446c38e081908cdaf113bdf86790 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd7c1fa01081909d589686289b624b completed March 20, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69befe9691608190bae0865f80e23062 completed March 21, 2026, 8:24 p.m.
Created at: March 20, 2026, 1:51 p.m.