Triple

T6426047
Position Surface form Disambiguated ID Type / Status
Subject Trondheimsfjord E128059 entity
Predicate adjacentTo P224 FINISHED
Object Frosta E455318 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: Frosta | Statement: [Trondheimsfjord, adjacentTo, Frosta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frosta
Context triple: [Trondheimsfjord, adjacentTo, Frosta]
  • A. Frosta chosen
    Frosta is a rural municipality and peninsula in Trøndelag county, Norway, known for its fertile farmland and historical significance as a medieval assembly site.
  • B. Felindre
    Felindre is a small rural village in Wales situated within the City and County of Swansea, known for its scenic surroundings and traditional community character.
  • C. Balfrin
    Balfrin is a prominent alpine peak in the Swiss Pennine Alps, known for its glaciated slopes and location near the Mischabel range.
  • D. Frogn
    Frogn is a coastal municipality in Viken county, Norway, known for the historic Oscarsborg Fortress in the Oslofjord.
  • E. Fasenra
    Fasenra is a monoclonal antibody medication used to treat severe eosinophilic asthma by targeting and reducing eosinophil levels.
  • 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.