Triple

T16027179
Position Surface form Disambiguated ID Type / Status
Subject Bremanger E388745 entity
Predicate administrativeCentre P1474 FINISHED
Object Svelgen
Svelgen is a small village in Vestland county, Norway, known as an industrial community and local hub at the mouth of the Svelgselva river.
E1189202 NE FINISHED

How this triple was built (4 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: Svelgen | Statement: [Bremanger, administrativeCentre, Svelgen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Svelgen
Context triple: [Bremanger, administrativeCentre, Svelgen]
  • A. Sveg
    Sveg is a small town in central Sweden known as an administrative and service hub in the sparsely populated province of Härjedalen.
  • B. Svaneke
    Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
  • C. Veidnes
    Veidnes is a small coastal village located in the municipality of Lebesby in northern Norway.
  • D. Guttannen
    Guttannen is a small Swiss mountain municipality in the Bernese Oberland, known for its alpine landscapes and location along the upper Aare River.
  • E. Selänne
    Selänne is the surname of Teemu Selänne, a legendary Finnish ice hockey player and one of the NHL’s most prolific goal scorers.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Svelgen
Triple: [Bremanger, administrativeCentre, Svelgen]
Generated description
Svelgen is a small village in Vestland county, Norway, known as an industrial community and local hub at the mouth of the Svelgselva river.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Svelgen
Target entity description: Svelgen is a small village in Vestland county, Norway, known as an industrial community and local hub at the mouth of the Svelgselva river.
  • A. Sveg
    Sveg is a small town in central Sweden known as an administrative and service hub in the sparsely populated province of Härjedalen.
  • B. Svaneke
    Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
  • C. Veidnes
    Veidnes is a small coastal village located in the municipality of Lebesby in northern Norway.
  • D. Guttannen
    Guttannen is a small Swiss mountain municipality in the Bernese Oberland, known for its alpine landscapes and location along the upper Aare River.
  • E. Selänne
    Selänne is the surname of Teemu Selänne, a legendary Finnish ice hockey player and one of the NHL’s most prolific goal scorers.
  • F. None of above. chosen

Provenance (5 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_69d86dada3808190825d5f80d72fbe88 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e18328707c8190b9a444c78faaaa04 completed April 17, 2026, 12:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffcf33c6a881909284933ea3b7dd6e completed May 10, 2026, 12:20 a.m.
NEDg Description generation batch_69ffd01d545c8190a96cd888223c7fa9 completed May 10, 2026, 12:23 a.m.
NED2 Entity disambiguation (via description) batch_69ffd0b3d4b08190b1be30954d5d76c0 completed May 10, 2026, 12:26 a.m.
Created at: April 10, 2026, 4:56 a.m.