Triple

T15889752
Position Surface form Disambiguated ID Type / Status
Subject Lakselv E385284 entity
Predicate locatedOnRiver P165 FINISHED
Object Lakselva E382086 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: Lakselva | Statement: [Lakselv, locatedOnRiver, Lakselva]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lakselva
Context triple: [Lakselv, locatedOnRiver, Lakselva]
  • A. Lakselva chosen
    Lakselva is a river in northern Norway known for its rich salmon fishing and scenic Arctic landscapes.
  • B. Fykseelva
    Fykseelva is a river flowing through the municipality of Kvam in Vestland county, western Norway, known for its scenic valley and salmon fishing.
  • C. Lakselv
    Lakselv is a small town in northern Norway that serves as an administrative and transport hub in Finnmark, near the Porsangerfjorden and close to the North Cape region.
  • D. Målselva
    Målselva is a major river in Troms, northern Norway, known for its salmon fishing and scenic valley landscapes.
  • E. Lærdalselvi
    Lærdalselvi is a renowned salmon river in western Norway, flowing through the Lærdal valley to the Sognefjord and known for both its fishing and scenic landscape.
  • 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_69d86da5b800819083a31be937d738b0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1561d5c28819094c3541d917a4433 completed April 16, 2026, 9:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffeb7f3c9481908bdde67998263c5e completed May 10, 2026, 2:20 a.m.
Created at: April 10, 2026, 4:51 a.m.