Triple

T5843425
Position Surface form Disambiguated ID Type / Status
Subject Verdal E129647 entity
Predicate hasNeighbor P5707 FINISHED
Object Levanger E517242 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: Levanger | Statement: [Verdal, hasNeighbor, Levanger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Levanger
Context triple: [Verdal, hasNeighbor, Levanger]
  • A. Levanger chosen
    Levanger is a historic town and municipality in Trøndelag county, Norway, known for its traditional wooden architecture and role as a regional commercial and educational center.
  • B. Lørenskog
    Lørenskog is a suburban municipality in Viken county, Norway, located just east of Oslo and known for its residential areas and commercial centers.
  • C. Tvedestrand
    Tvedestrand is a coastal town and municipality in southern Norway known for its wooden houses, maritime heritage, and picturesque archipelago.
  • D. Lyngdal
    Lyngdal is a coastal town and municipality in southern Norway known for its beaches, fjords, and tourism.
  • E. Larvik
    Larvik is a coastal town and municipality in Vestfold, Norway, known for its harbor, beaches, and historic connections to the shipping and timber industries.
  • 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_69c0084bd31c8190a796bb6284845e83 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c034d9da0c8190970319d0dc2fc73f completed March 22, 2026, 6:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69c673ea34ec81909b2391a690ed502e completed March 27, 2026, 12:11 p.m.
Created at: March 22, 2026, 3:54 p.m.