Triple

T14725044
Position Surface form Disambiguated ID Type / Status
Subject Søndre Land E345916 entity
Predicate bordersWith P224 FINISHED
Object Nordre Land E434824 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: Nordre Land | Statement: [Søndre Land, bordersWith, Nordre Land]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nordre Land
Context triple: [Søndre Land, bordersWith, Nordre Land]
  • A. Nordre Land chosen
    Nordre Land is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and agricultural landscape in the traditional district of Land.
  • B. Nordlandet
    Nordlandet is one of the main islands and districts of the coastal Norwegian city of Kristiansund.
  • C. Helgeland
    Helgeland is a coastal region in northern Norway known for its dramatic fjords, islands, and mountain landscapes.
  • D. Vestlandet
    Vestlandet is the western region of Norway, known for its dramatic fjords, mountains, and coastal landscapes.
  • E. Nordmøre
    Nordmøre is a traditional district in the northern part of Møre og Romsdal county in western Norway, known for its coastal landscapes, fjords, and fishing communities.
  • 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_69d822e5911c8190ba589f957dbd9ba7 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec25e9a14819081fa06fc601f295d completed April 14, 2026, 10:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe6b43360481908dc73d5e6758fea6 completed May 8, 2026, 11:01 p.m.
Created at: April 10, 2026, 1:29 a.m.