Triple

T13528550
Position Surface form Disambiguated ID Type / Status
Subject Avaldsnes IL E323072 entity
Predicate basedIn P40 FINISHED
Object Avaldsnes E376431 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: Avaldsnes | Statement: [Avaldsnes IL, basedIn, Avaldsnes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Avaldsnes
Context triple: [Avaldsnes IL, basedIn, Avaldsnes]
  • A. Avaldsnes chosen
    Avaldsnes is a historic village in Rogaland county, Norway, known as one of the country’s oldest royal seats and a key center in Viking-era history.
  • B. Alstahaug
    Alstahaug is a coastal municipality in northern Norway known for its historic church, island landscapes, and maritime heritage.
  • C. Orkanger
    Orkanger is a town in Trøndelag county, Norway, known as a regional commercial and service hub by the Orkdalsfjorden.
  • D. Åndalsnes
    Åndalsnes is a small Norwegian town known as a gateway to dramatic fjord and mountain landscapes, including popular hiking and climbing areas like Romsdalseggen and Trollveggen.
  • E. Namdalseid
    Namdalseid is a former rural municipality in Trøndelag county, Norway, known for its forests, agriculture, and coastal landscape along the Namsenfjorden.
  • 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafb8e0cc8190b47f6aeb8ced470e completed April 12, 2026, 2:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69f76ba9fccc81908ec2e33d66aae8ea completed May 3, 2026, 3:37 p.m.
Created at: April 9, 2026, 9:44 p.m.