Triple

T10635733
Position Surface form Disambiguated ID Type / Status
Subject Nesodden E250574 entity
Predicate capital P234 FINISHED
Object Nesoddtangen E670527 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: Nesoddtangen | Statement: [Nesodden, capital, Nesoddtangen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nesoddtangen
Context triple: [Nesodden, capital, Nesoddtangen]
  • A. Nesoddtangen chosen
    Nesoddtangen is a village and administrative center in Nesodden municipality in Viken county, Norway, located on a peninsula directly across the Oslofjord from central Oslo.
  • B. Hisingen
    Hisingen is a large island and district in Gothenburg, Sweden, known for its industrial areas, shipyards, and rapidly developing residential and tech hubs.
  • C. Bispevika
    Bispevika is a redeveloped waterfront district in Oslo, Norway, featuring modern residential, commercial, and cultural spaces along the city’s inner harbor.
  • D. Asmaløy
    Asmaløy is one of the main inhabited islands in the Hvaler archipelago in southeastern Norway, known for its coastal scenery and holiday homes.
  • E. Brattvåg
    Brattvåg is a small coastal village in western Norway known for its maritime industry and scenic fjord 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_69d6aa5993448190a493b790b8f85010 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6dfac70f481908363f9ac0b651fbe completed April 8, 2026, 11:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69d998a4571481908f5010146f7ca5d7 completed April 11, 2026, 12:41 a.m.
Created at: April 8, 2026, 9:03 p.m.