Triple

T16027188
Position Surface form Disambiguated ID Type / Status
Subject Bremanger E388745 entity
Predicate hasSettlement P1068 FINISHED
Object Ålfoten
Ålfoten is a small village in Bremanger Municipality in Vestland county, western Norway, known for its fjord-side setting and surrounding mountainous landscape.
E1189205 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: Ålfoten | Statement: [Bremanger, hasSettlement, Ålfoten]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ålfoten
Context triple: [Bremanger, hasSettlement, Ålfoten]
  • A. Lysthaugen
    Lysthaugen is a small settlement located in the municipality of Verdal in Trøndelag county, Norway.
  • B. Årdalstangen
    Årdalstangen is a village in Vestland county, Norway, known for its industrial activity and location at the end of the Årdalsfjorden.
  • C. Tallkrogen
    Tallkrogen is a residential district in southern Stockholm, Sweden, known for its small-scale housing and garden-city character.
  • D. Skarvehøi
    Skarvehøi is a mountain located in Lesja municipality in Innlandet county, Norway, known for its alpine terrain and scenic hiking opportunities.
  • E. Hodnefjell
    Hodnefjell is an island that forms part of the Finnøy archipelago in 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: Ålfoten
Triple: [Bremanger, hasSettlement, Ålfoten]
Generated description
Ålfoten is a small village in Bremanger Municipality in Vestland county, western Norway, known for its fjord-side setting and surrounding mountainous landscape.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Ålfoten
Target entity description: Ålfoten is a small village in Bremanger Municipality in Vestland county, western Norway, known for its fjord-side setting and surrounding mountainous landscape.
  • A. Lysthaugen
    Lysthaugen is a small settlement located in the municipality of Verdal in Trøndelag county, Norway.
  • B. Årdalstangen
    Årdalstangen is a village in Vestland county, Norway, known for its industrial activity and location at the end of the Årdalsfjorden.
  • C. Tallkrogen
    Tallkrogen is a residential district in southern Stockholm, Sweden, known for its small-scale housing and garden-city character.
  • D. Skarvehøi
    Skarvehøi is a mountain located in Lesja municipality in Innlandet county, Norway, known for its alpine terrain and scenic hiking opportunities.
  • E. Hodnefjell
    Hodnefjell is an island that forms part of the Finnøy archipelago in 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.