Triple
T10428321
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nannestad |
E245842
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object |
Steinråa
Steinråa is a small settlement located in Nannestad municipality in Viken county, Norway.
|
E875778
|
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: Steinråa | Statement: [Nannestad, hasSettlement, Steinråa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steinråa Context triple: [Nannestad, hasSettlement, Steinråa]
-
A.
Bekkestua
Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
-
B.
Sørreisa
Sørreisa is a small coastal municipality and village area in northern Norway known for its fjords and rural Arctic landscape.
-
C.
Sørenga
Sørenga is a modern waterfront neighborhood in Oslo, Norway, known for its residential developments, seaside promenade, and popular public seawater pool and beach.
-
D.
Stenåsa
Stenåsa is a small village on the island of Öland in southeastern Sweden, known for its rural landscape and proximity to coastal and natural areas.
-
E.
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.
- 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: Steinråa Triple: [Nannestad, hasSettlement, Steinråa]
Generated description
Steinråa is a small settlement located in Nannestad municipality in Viken county, Norway.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Steinråa Target entity description: Steinråa is a small settlement located in Nannestad municipality in Viken county, Norway.
-
A.
Bekkestua
Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
-
B.
Sørreisa
Sørreisa is a small coastal municipality and village area in northern Norway known for its fjords and rural Arctic landscape.
-
C.
Sørenga
Sørenga is a modern waterfront neighborhood in Oslo, Norway, known for its residential developments, seaside promenade, and popular public seawater pool and beach.
-
D.
Stenåsa
Stenåsa is a small village on the island of Öland in southeastern Sweden, known for its rural landscape and proximity to coastal and natural areas.
-
E.
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.
- 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_69d96b2803d88190ab93dd19b4cfee30 |
completed | April 10, 2026, 9:27 p.m. |
| NEDg | Description generation | batch_69d96dee84f48190bf5b0cb1115a8bba |
completed | April 10, 2026, 9:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d9708824208190acf75933962d690f |
completed | April 10, 2026, 9:50 p.m. |
Created at: April 6, 2026, 12:13 p.m.