Triple

T6426012
Position Surface form Disambiguated ID Type / Status
Subject Trondheimsfjord E128059 entity
Predicate hasCityOnShore P969 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: [Trondheimsfjord, hasCityOnShore, Levanger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Levanger
Context triple: [Trondheimsfjord, hasCityOnShore, 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. Slemdal
    Slemdal is a residential neighborhood in the Vestre Aker borough of Oslo, Norway, known for its green surroundings and affluent character.
  • C. Lørenskog
    Lørenskog is a suburban municipality in Viken county, Norway, located just east of Oslo and known for its residential areas and commercial centers.
  • D. Tvedestrand
    Tvedestrand is a coastal town and municipality in southern Norway known for its wooden houses, maritime heritage, and picturesque archipelago.
  • E. Lyngdal
    Lyngdal is a coastal town and municipality in southern Norway known for its beaches, fjords, and tourism.
  • 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_69c00838de888190af2eec0b80495efa completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0691f944c81909d4e5d8ef9e494b6 completed March 22, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8ac74f44c8190953e486d3a315a64 completed March 29, 2026, 4:37 a.m.
Created at: March 22, 2026, 4:43 p.m.