Triple
T15302544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kvam |
E365823
|
entity |
| Predicate | includesVillage |
P4011
|
FINISHED |
| Object |
Ålvik
Ålvik is a small industrial village in Kvam municipality in Vestland county, western Norway, known historically for its ferroalloy production and scenic fjordside setting.
|
E1180810
|
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: Ålvik | Statement: [Kvam, includesVillage, Ålvik]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ålvik Context triple: [Kvam, includesVillage, Ålvik]
-
A.
Alvdal
Alvdal is a rural municipality in Innlandet county, Norway, known for its agricultural landscape, outdoor recreation, and association with the author Kjell Aukrust.
-
B.
Håvik
Håvik is a small coastal village located in Karmøy municipality in Rogaland county, southwestern Norway.
-
C.
Tingvoll
Tingvoll is a small municipality and village area in western Norway known for its rural landscape, fjords, and agricultural traditions.
-
D.
Åkrehamn
Åkrehamn is a coastal town in southwestern Norway known for its fishing industry and scenic North Sea shoreline.
-
E.
Røyrvik
Røyrvik is a small rural municipality in Trøndelag county, Norway, known for its mountainous landscapes, reindeer herding traditions, and proximity to Børgefjell National Park.
- 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: Ålvik Triple: [Kvam, includesVillage, Ålvik]
Generated description
Ålvik is a small industrial village in Kvam municipality in Vestland county, western Norway, known historically for its ferroalloy production and scenic fjordside setting.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ålvik Target entity description: Ålvik is a small industrial village in Kvam municipality in Vestland county, western Norway, known historically for its ferroalloy production and scenic fjordside setting.
-
A.
Alvdal
Alvdal is a rural municipality in Innlandet county, Norway, known for its agricultural landscape, outdoor recreation, and association with the author Kjell Aukrust.
-
B.
Håvik
Håvik is a small coastal village located in Karmøy municipality in Rogaland county, southwestern Norway.
-
C.
Tingvoll
Tingvoll is a small municipality and village area in western Norway known for its rural landscape, fjords, and agricultural traditions.
-
D.
Åkrehamn
Åkrehamn is a coastal town in southwestern Norway known for its fishing industry and scenic North Sea shoreline.
-
E.
Røyrvik
Røyrvik is a small rural municipality in Trøndelag county, Norway, known for its mountainous landscapes, reindeer herding traditions, and proximity to Børgefjell National Park.
- 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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03ccd575c8190aa43262d3b73ef3c |
completed | April 16, 2026, 1:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa92e5f5c81908f54e91b7f16607e |
completed | May 9, 2026, 9:37 p.m. |
| NEDg | Description generation | batch_69ffaa279e888190a1c8d95a10b77766 |
completed | May 9, 2026, 9:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffaaa92a648190a09829ef3197223c |
completed | May 9, 2026, 9:44 p.m. |
Created at: April 10, 2026, 3:15 a.m.