Triple
T10462257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bamble |
E246703
|
entity |
| Predicate | neighbouringMunicipality |
P33892
|
FINISHED |
| Object | Drangedal |
E689896
|
NE FINISHED |
How this triple was built (2 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: Drangedal | Statement: [Bamble, neighbouringMunicipality, Drangedal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Drangedal Context triple: [Bamble, neighbouringMunicipality, Drangedal]
-
A.
Engerdal
Engerdal is a sparsely populated municipality in Innlandet county, Norway, known for its vast forests, lakes, and proximity to the Swedish border.
-
B.
Orkdal
Orkdal was a former municipality in Trøndelag county, Norway, known for its central location in the Orkdalen valley and later incorporation into the larger Orkland municipality.
-
C.
Nissedal
chosen
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
-
D.
Nadderud
Nadderud is a residential and sports-focused area in Bærum, Norway, known for its stadium and athletic facilities.
-
E.
Gjerdrum
Gjerdrum is a small rural municipality in Viken county, Norway, known for its agricultural landscape and proximity to the Oslo metropolitan area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d50884fac48190af22e181b1492557 |
completed | April 7, 2026, 1:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3a8e98cac8190873af1a2cdb5c5a9 |
completed | April 18, 2026, 3:53 p.m. |
Created at: April 6, 2026, 12:19 p.m.