Triple

T16027250
Position Surface form Disambiguated ID Type / Status
Subject Vågsøy E388746 entity
Predicate hasVillage P4011 FINISHED
Object Bryggja
Bryggja is a small coastal village in the former Vågsøy municipality in Vestland county, western Norway.
E1189215 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: Bryggja | Statement: [Vågsøy, hasVillage, Bryggja]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bryggja
Context triple: [Vågsøy, hasVillage, Bryggja]
  • A. Hjelteryggen
    Hjelteryggen is a small settlement located in Fjell municipality in Vestland county on the western coast of Norway.
  • B. Gildeskål
    Gildeskål is a coastal municipality in Nordland county, Norway, known for its fishing communities, scenic islands, and historic stone church.
  • C. Skibotn
    Skibotn is a small village in northern Norway known for its clear skies and role as a center for astronomical observations.
  • D. Skudeneshavn
    Skudeneshavn is a historic coastal town in southwestern Norway known for its well-preserved wooden architecture and maritime heritage.
  • E. Sjøbadet
    Sjøbadet is a popular public beach and recreational seaside area in the coastal town of Moss, Norway.
  • 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: Bryggja
Triple: [Vågsøy, hasVillage, Bryggja]
Generated description
Bryggja is a small coastal village in the former Vågsøy municipality in Vestland county, western Norway.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Bryggja
Target entity description: Bryggja is a small coastal village in the former Vågsøy municipality in Vestland county, western Norway.
  • A. Hjelteryggen
    Hjelteryggen is a small settlement located in Fjell municipality in Vestland county on the western coast of Norway.
  • B. Gildeskål
    Gildeskål is a coastal municipality in Nordland county, Norway, known for its fishing communities, scenic islands, and historic stone church.
  • C. Skibotn
    Skibotn is a small village in northern Norway known for its clear skies and role as a center for astronomical observations.
  • D. Skudeneshavn
    Skudeneshavn is a historic coastal town in southwestern Norway known for its well-preserved wooden architecture and maritime heritage.
  • E. Sjøbadet
    Sjøbadet is a popular public beach and recreational seaside area in the coastal town of Moss, Norway.
  • 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.