Triple
T2912323
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Froland |
E63709
|
entity |
| Predicate | neighbouringMunicipality |
P33892
|
FINISHED |
| Object |
Birkenes
Birkenes is a rural municipality in Agder county in southern Norway, known for its forests, rivers, and small villages.
|
E308960
|
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: Birkenes | Statement: [Froland, neighbouringMunicipality, Birkenes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Birkenes Context triple: [Froland, neighbouringMunicipality, Birkenes]
-
A.
Bekkestua
Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
-
B.
Bolnes
Bolnes is a Dutch surname most notably associated with Catharina Bolnes, the wife of painter Johannes Vermeer.
-
C.
Eiderstedt
Eiderstedt is a low-lying peninsula on Germany’s North Sea coast known for its dike-protected marshlands, agriculture, and coastal tourism.
-
D.
Brevik
Brevik is a locality within Tyresö Municipality in Stockholm County, Sweden, known for its coastal residential areas and proximity to the Stockholm archipelago.
-
E.
Svaneke
Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
- 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: Birkenes Triple: [Froland, neighbouringMunicipality, Birkenes]
Generated description
Birkenes is a rural municipality in Agder county in southern Norway, known for its forests, rivers, and small villages.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Birkenes Target entity description: Birkenes is a rural municipality in Agder county in southern Norway, known for its forests, rivers, and small villages.
-
A.
Bekkestua
Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
-
B.
Bolnes
Bolnes is a Dutch surname most notably associated with Catharina Bolnes, the wife of painter Johannes Vermeer.
-
C.
Eiderstedt
Eiderstedt is a low-lying peninsula on Germany’s North Sea coast known for its dike-protected marshlands, agriculture, and coastal tourism.
-
D.
Brevik
Brevik is a locality within Tyresö Municipality in Stockholm County, Sweden, known for its coastal residential areas and proximity to the Stockholm archipelago.
-
E.
Svaneke
Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
- 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_69ab4c44ab448190b9411324e8a1fc1d |
completed | March 6, 2026, 9:51 p.m. |
| NER | Named-entity recognition | batch_69abe0eb77708190b745b887f3b9a618 |
completed | March 7, 2026, 8:25 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b0562014fc8190b7b702fa40682382 |
completed | March 10, 2026, 5:34 p.m. |
| NEDg | Description generation | batch_69b05f7e78e8819095185f170ca26bda |
completed | March 10, 2026, 6:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b0617a21a881909a0f52268a2494a6 |
completed | March 10, 2026, 6:22 p.m. |
Created at: March 6, 2026, 10:11 p.m.