Triple

T6426028
Position Surface form Disambiguated ID Type / Status
Subject Trondheimsfjord E128059 entity
Predicate drainedByRiver P4497 FINISHED
Object Nidelva E567375 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: Nidelva | Statement: [Trondheimsfjord, drainedByRiver, Nidelva]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nidelva
Context triple: [Trondheimsfjord, drainedByRiver, Nidelva]
  • A. Nidelva chosen
    Nidelva is the main river flowing through Trondheim, Norway, known for its scenic bends, historic waterfront buildings, and central role in the city’s landscape.
  • B. Nidelva river
    Nidelva river is a river in southern Norway that flows through the county of Agder, including the municipality of Froland, before reaching the city of Arendal and the Skagerrak coast.
  • C. Nesset
    Nesset is a former municipality in western Norway known for its scenic fjord landscapes and rural communities.
  • D. Eidselva
    Eidselva is a river in Norway that serves as one of the main waterways feeding into the lake Norsjø.
  • 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 (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_69c00838de888190af2eec0b80495efa completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0691f944c81909d4e5d8ef9e494b6 completed March 22, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c64bbc865c81909bf064b9253bc263 completed March 27, 2026, 9:19 a.m.
Created at: March 22, 2026, 4:43 p.m.