Triple

T14601488
Position Surface form Disambiguated ID Type / Status
Subject Stange E342714 entity
Predicate hasVillage P4011 FINISHED
Object Ilseng E1061831 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: Ilseng | Statement: [Stange, hasVillage, Ilseng]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ilseng
Context triple: [Stange, hasVillage, Ilseng]
  • A. Ilseng chosen
    Ilseng is a small village in Innlandet county, Norway, known for its rural setting and proximity to the town of Hamar.
  • B. Tongrinne
    Tongrinne is a village in the Walloon region of Belgium that forms one of the municipal sections of the municipality of Sombreffe in the province of Namur.
  • C. Ulsrud
    Ulsrud is a residential neighborhood in the Østensjø borough of Oslo, Norway, known for its proximity to Ulsrudvannet lake and access to public transportation.
  • D. Brynseng
    Brynseng is a neighborhood and transport hub in Oslo, Norway, served by the Oslo Metro and other public transit connections.
  • E. Oltedal
    Oltedal is a small village in Rogaland county, Norway, known for its scenic surroundings and role as a local residential and industrial community within Gjesdal municipality.
  • 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_69d822dec68081908c2553145c4051dc completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb438748081908020ce04b869866a completed April 14, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd94cc9fbc819090ae4efe9bc618aa completed May 8, 2026, 7:46 a.m.
Created at: April 10, 2026, 1:25 a.m.