Triple
T6869335
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Øvre Eiker |
E158498
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Ormåsen
Ormåsen is a small residential village in Øvre Eiker municipality in Buskerud county, Norway.
|
E627511
|
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: Ormåsen | Statement: [Øvre Eiker, hasSettlement, Ormåsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ormåsen Context triple: [Øvre Eiker, hasSettlement, Ormåsen]
-
A.
Byåsen
Byåsen is a largely residential hillside district in Trondheim, Norway, known for its scenic views over the city and access to outdoor recreation areas.
-
B.
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.
-
C.
Bekkestua
Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
-
D.
Møysalen
Møysalen is a prominent mountain in northern Norway known for its rugged alpine scenery and popular hiking routes.
-
E.
Bergshamra
Bergshamra is a residential district in the northern Stockholm urban area of Sweden, known for its proximity to green spaces and good public transport connections.
- 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: Ormåsen Triple: [Øvre Eiker, hasSettlement, Ormåsen]
Generated description
Ormåsen is a small residential village in Øvre Eiker municipality in Buskerud county, Norway.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ormåsen Target entity description: Ormåsen is a small residential village in Øvre Eiker municipality in Buskerud county, Norway.
-
A.
Byåsen
Byåsen is a largely residential hillside district in Trondheim, Norway, known for its scenic views over the city and access to outdoor recreation areas.
-
B.
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.
-
C.
Bekkestua
Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
-
D.
Møysalen
Møysalen is a prominent mountain in northern Norway known for its rugged alpine scenery and popular hiking routes.
-
E.
Bergshamra
Bergshamra is a residential district in the northern Stockholm urban area of Sweden, known for its proximity to green spaces and good public transport connections.
- 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_69c68831e3648190a643c328122e4d43 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d8a916a88190b81551731dff2898 |
completed | March 27, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c748c0689081908d37d1530ed0f6a0 |
completed | March 28, 2026, 3:19 a.m. |
| NEDg | Description generation | batch_69c749741dd08190b268303a12c17b66 |
completed | March 28, 2026, 3:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c74a1935b88190a9bed6e73f730459 |
completed | March 28, 2026, 3:25 a.m. |
Created at: March 27, 2026, 2:22 p.m.