Triple
T15042494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stord |
E378635
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Sagvåg
Sagvåg is a village on the island municipality of Stord in Vestland county, Norway, known for its coastal setting and local maritime industry.
|
E1143789
|
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: Sagvåg | Statement: [Stord, hasSettlement, Sagvåg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sagvåg Context triple: [Stord, hasSettlement, Sagvåg]
-
A.
Vikevåg
Vikevåg is a village in Rogaland county, Norway, known for its coastal setting and role in local administration and services.
-
B.
Brattvåg
Brattvåg is a small coastal village in western Norway known for its maritime industry and scenic fjord landscape.
-
C.
Fosnavåg
Fosnavåg is a small coastal town in western Norway known for its maritime industries and scenic North Sea surroundings.
-
D.
Vikersund
Vikersund is a village in Modum municipality in Buskerud, Norway, best known for hosting one of the world’s largest ski flying hills, Vikersundbakken.
-
E.
Kårvåg
Kårvåg is a small coastal village in western Norway, known as a settlement on the island of Averøya in Møre og Romsdal county.
- 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: Sagvåg Triple: [Stord, hasSettlement, Sagvåg]
Generated description
Sagvåg is a village on the island municipality of Stord in Vestland county, Norway, known for its coastal setting and local maritime industry.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sagvåg Target entity description: Sagvåg is a village on the island municipality of Stord in Vestland county, Norway, known for its coastal setting and local maritime industry.
-
A.
Vikevåg
Vikevåg is a village in Rogaland county, Norway, known for its coastal setting and role in local administration and services.
-
B.
Brattvåg
Brattvåg is a small coastal village in western Norway known for its maritime industry and scenic fjord landscape.
-
C.
Fosnavåg
Fosnavåg is a small coastal town in western Norway known for its maritime industries and scenic North Sea surroundings.
-
D.
Vikersund
Vikersund is a village in Modum municipality in Buskerud, Norway, best known for hosting one of the world’s largest ski flying hills, Vikersundbakken.
-
E.
Kårvåg
Kårvåg is a small coastal village in western Norway, known as a settlement on the island of Averøya in Møre og Romsdal county.
- 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_69d85cd46b2c819090d054c27787f677 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded82f73208190bb55fa6b20074e27 |
completed | April 15, 2026, 12:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fed31debb48190908d59178e67adb6 |
completed | May 9, 2026, 6:24 a.m. |
| NEDg | Description generation | batch_69fed50514b08190bc50d2e700d82e69 |
completed | May 9, 2026, 6:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fed5693ff08190b16b4c8fc8bdf959 |
completed | May 9, 2026, 6:34 a.m. |
Created at: April 10, 2026, 3 a.m.