Triple

T10428302
Position Surface form Disambiguated ID Type / Status
Subject Nannestad E245842 entity
Predicate administrativeCentre P1474 FINISHED
Object Nannestad sentrum E570237 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: Nannestad sentrum | Statement: [Nannestad, administrativeCentre, Nannestad sentrum]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nannestad sentrum
Context triple: [Nannestad, administrativeCentre, Nannestad sentrum]
  • A. Nannestad chosen
    Nannestad is a rural municipality in Viken county, Norway, known for its agricultural landscape and proximity to Oslo Airport Gardermoen.
  • B. Smestad
    Smestad is a residential neighborhood in Oslo, Norway, known for its affluent housing and proximity to green areas and good public transport.
  • C. municipality of Nannestad
    The municipality of Nannestad is a local government area in southeastern Norway known for its rural landscapes, agriculture, and proximity to Oslo Airport Gardermoen.
  • D. Rubbestadneset
    Rubbestadneset is a village in the municipality of Bømlo in Vestland county, on the western coast of Norway.
  • E. Myklebostad
    Myklebostad is a small village located on the island of Tjeldøya in northern Norway.
  • 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_69d381bf3dc08190bf35a2643e4e8f22 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4ea4a7dcc81909a830e08656a1c0c completed April 7, 2026, 11:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7fc2b50b48190b1d5b29d19a240c2 completed April 9, 2026, 7:21 p.m.
Created at: April 6, 2026, 12:13 p.m.