Triple

T17339449
Position Surface form Disambiguated ID Type / Status
Subject Romerike E421025 entity
Predicate hasRiver P165 FINISHED
Object Glomma 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: Glomma | Statement: [Romerike, hasRiver, Glomma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Glomma
Context triple: [Romerike, hasRiver, Glomma]
  • A. Glomma chosen
    Glomma is Norway’s longest and largest river, flowing through Eastern Norway before emptying into the Oslofjord.
  • B. Drammenselva
    Drammenselva is a major river in southeastern Norway known for its historical timber floating, hydroelectric power production, and salmon fishing.
  • C. Saltdalselva
    Saltdalselva is a river in Nordland county, Norway, known for flowing through the Saltdal valley and offering notable salmon fishing and scenic natural landscapes.
  • D. Stjørdalselva
    Stjørdalselva is a river in Trøndelag county, Norway, known for flowing through the Stjørdal valley and being a popular destination for salmon fishing.
  • E. Moldeelva
    Moldeelva is a river flowing through the Norwegian town of Molde, contributing to its landscape and local environment.
  • 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_69d889d3adc881909319f1edb8d2a956 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a14ec90819098db2ac0d58a53e1 completed April 19, 2026, 2:12 a.m.
Created at: April 10, 2026, 5:44 a.m.