Triple
T4434673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buskerud |
E95618
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Røyken
Røyken is a former municipality and suburban area in southeastern Norway, located along the Oslofjord and historically part of Buskerud county.
|
E489438
|
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: Røyken | Statement: [Buskerud, contains, Røyken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Røyken Context triple: [Buskerud, contains, Røyken]
-
A.
Gjøvik
Gjøvik is a town and municipality in Innlandet county, Norway, known for its location along Lake Mjøsa and its mix of industrial heritage and modern sports and cultural facilities.
-
B.
Lørenskog
Lørenskog is a suburban municipality in Viken county, Norway, located just east of Oslo and known for its residential areas and commercial centers.
-
C.
Drammen
Drammen is a city and municipality in southeastern Norway known for its riverside setting along the Drammenselva and its role as a regional commercial and transport hub.
-
D.
Risør
Risør is a small coastal town in southern Norway known for its well-preserved wooden houses, maritime heritage, and annual wooden boat festival.
-
E.
Sandnes
Sandnes is a city in southwestern Norway, near Stavanger, known for its proximity to fjords and outdoor recreation areas.
- 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: Røyken Triple: [Buskerud, contains, Røyken]
Generated description
Røyken is a former municipality and suburban area in southeastern Norway, located along the Oslofjord and historically part of Buskerud county.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Røyken Target entity description: Røyken is a former municipality and suburban area in southeastern Norway, located along the Oslofjord and historically part of Buskerud county.
-
A.
Gjøvik
Gjøvik is a town and municipality in Innlandet county, Norway, known for its location along Lake Mjøsa and its mix of industrial heritage and modern sports and cultural facilities.
-
B.
Lørenskog
Lørenskog is a suburban municipality in Viken county, Norway, located just east of Oslo and known for its residential areas and commercial centers.
-
C.
Drammen
Drammen is a city and municipality in southeastern Norway known for its riverside setting along the Drammenselva and its role as a regional commercial and transport hub.
-
D.
Risør
Risør is a small coastal town in southern Norway known for its well-preserved wooden houses, maritime heritage, and annual wooden boat festival.
-
E.
Sandnes
Sandnes is a city in southwestern Norway, near Stavanger, known for its proximity to fjords and outdoor recreation areas.
- 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_69b3453ea2b48190a26f154b3b8fece5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35588e99881908fea7b71a33e2bb6 |
completed | March 13, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bea45c53908190af21d54dbf9550f0 |
completed | March 21, 2026, 1:59 p.m. |
| NEDg | Description generation | batch_69bea4d632f881909e621f5d11855f8b |
completed | March 21, 2026, 2:01 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bea547a08c8190ae74293c4a729ad2 |
completed | March 21, 2026, 2:03 p.m. |
Created at: March 12, 2026, 11:31 p.m.