Triple
T20018750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rissa (former municipality) |
E494791
|
entity |
| Predicate | administrativeCentre |
P1474
|
FINISHED |
| Object |
Årnset
Årnset is a village in Trøndelag county, Norway, known for serving as the central settlement of the Rissa area.
|
E1441214
|
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: Årnset | Statement: [Rissa (former municipality), administrativeCentre, Årnset]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Årnset Context triple: [Rissa (former municipality), administrativeCentre, Årnset]
-
A.
Årnes
Årnes is a small Norwegian town situated along the Glomma River, known as a local administrative and commercial center in Nes municipality in Viken county.
-
B.
Tynset
Tynset is a rural municipality in Innlandet county, Norway, known for its vast mountain landscapes, agriculture, and role as a regional service center in the Østerdalen valley.
-
C.
Åråsen
Åråsen is a football stadium in Lillestrøm, Norway, best known as the home ground of Lillestrøm SK.
-
D.
Åraksbø
Åraksbø is a small village in southern Norway located within the municipality of Bygland in Agder county.
-
E.
Vangsnes
Vangsnes is a small village in Vestland county, Norway, situated along the Sognefjorden and known for its scenic fjord landscape and agricultural surroundings.
- 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: Årnset Triple: [Rissa (former municipality), administrativeCentre, Årnset]
Generated description
Årnset is a village in Trøndelag county, Norway, known for serving as the central settlement of the Rissa area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Årnset Target entity description: Årnset is a village in Trøndelag county, Norway, known for serving as the central settlement of the Rissa area.
-
A.
Årnes
Årnes is a small Norwegian town situated along the Glomma River, known as a local administrative and commercial center in Nes municipality in Viken county.
-
B.
Tynset
Tynset is a rural municipality in Innlandet county, Norway, known for its vast mountain landscapes, agriculture, and role as a regional service center in the Østerdalen valley.
-
C.
Åråsen
Åråsen is a football stadium in Lillestrøm, Norway, best known as the home ground of Lillestrøm SK.
-
D.
Åraksbø
Åraksbø is a small village in southern Norway located within the municipality of Bygland in Agder county.
-
E.
Vangsnes
Vangsnes is a small village in Vestland county, Norway, situated along the Sognefjorden and known for its scenic fjord landscape and agricultural surroundings.
- 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_69da626bfd288190aa5d65098b6433ae |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6623e40748190b1abb0ead9acab4e |
completed | April 20, 2026, 5:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08bafc4c088190ae448e2cfca1de82 |
completed | May 16, 2026, 6:44 p.m. |
| NEDg | Description generation | batch_6a08bbddde1c81908733796442e6a562 |
completed | May 16, 2026, 6:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08bca1021c8190a0e89bad15e87bc1 |
completed | May 16, 2026, 6:51 p.m. |
Created at: April 11, 2026, 3:34 p.m.