Triple
T10428409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nes (Akershus) |
E245844
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Brårud
Brårud is a small village located within the municipality of Nes in Akershus county, Norway.
|
E882363
|
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: Brårud | Statement: [Nes (Akershus), hasSettlement, Brårud]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brårud Context triple: [Nes (Akershus), hasSettlement, Brårud]
-
A.
Bjugn
Bjugn is a former municipality and coastal community in Trøndelag county, Norway, known for its fishing, agriculture, and location on the Fosen peninsula.
-
B.
Nadderud
Nadderud is a residential and sports-focused area in Bærum, Norway, known for its stadium and athletic facilities.
-
C.
Suldal
Suldal is a large rural municipality in southwestern Norway known for its fjords, mountains, and hydroelectric power production.
-
D.
Mortensrud
Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
-
E.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
- 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: Brårud Triple: [Nes (Akershus), hasSettlement, Brårud]
Generated description
Brårud is a small village located within the municipality of Nes in Akershus county, Norway.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brårud Target entity description: Brårud is a small village located within the municipality of Nes in Akershus county, Norway.
-
A.
Bjugn
Bjugn is a former municipality and coastal community in Trøndelag county, Norway, known for its fishing, agriculture, and location on the Fosen peninsula.
-
B.
Nadderud
Nadderud is a residential and sports-focused area in Bærum, Norway, known for its stadium and athletic facilities.
-
C.
Suldal
Suldal is a large rural municipality in southwestern Norway known for its fjords, mountains, and hydroelectric power production.
-
D.
Mortensrud
Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
-
E.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
- 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_69d381bf3dc08190bf35a2643e4e8f22 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea4a7dcc81909a830e08656a1c0c |
completed | April 7, 2026, 11:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dbd966f0f08190a60ca3bcf0e08e98 |
completed | April 12, 2026, 5:41 p.m. |
| NEDg | Description generation | batch_69dcad07b51081908fd66ee9ff7341f6 |
completed | April 13, 2026, 8:44 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69dd4386e3308190bb8503ce75fa628f |
completed | April 13, 2026, 7:27 p.m. |
Created at: April 6, 2026, 12:13 p.m.