Triple

T6830866
Position Surface form Disambiguated ID Type / Status
Subject Kegums Hydroelectric Power Plant E157132 entity
Predicate locatedInRegion P40 FINISHED
Object Vidzeme E365504 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: Vidzeme | Statement: [Kegums Hydroelectric Power Plant, locatedInRegion, Vidzeme]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vidzeme
Context triple: [Kegums Hydroelectric Power Plant, locatedInRegion, Vidzeme]
  • A. Vidzeme chosen
    Vidzeme is a historical region in northern Latvia known for its rich cultural heritage, forests, and role in the development of Latvian national identity.
  • B. Kurzeme
    Kurzeme is a historical and cultural region in western Latvia, known for its Baltic Sea coastline, forests, and traditional Latvian heritage.
  • C. Vianen
    Vianen is a historic Dutch town known for its medieval city center and location near major rivers in the western Netherlands.
  • D. Tivissa
    Tivissa is a historic village in Catalonia, Spain, known for its scenic setting among the mountains of the Ribera d’Ebre region and its well-preserved medieval core.
  • E. Perejaume
    Perejaume is a contemporary Catalan artist and poet known for his conceptual explorations of landscape, language, and the relationship between art and territory.
  • 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_69c6882a5b5c8190917a7db9ed36bad1 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d62820808190ad3c244893e88699 completed March 27, 2026, 7:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c723f73eec81908c666888a19c0b29 completed March 28, 2026, 12:42 a.m.
Created at: March 27, 2026, 2:18 p.m.