Triple
T19198187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orkla |
E470025
|
entity |
| Predicate | mouthLocation |
P417
|
FINISHED |
| Object | Orkanger |
—
|
NE NERFINISHED |
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: Orkanger | Statement: [Orkla, mouthLocation, Orkanger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orkanger Context triple: [Orkla, mouthLocation, Orkanger]
-
A.
Orkanger
chosen
Orkanger is a town in Trøndelag county, Norway, known as a regional commercial and service hub by the Orkdalsfjorden.
-
B.
Ringerike
Ringerike is a historic district and municipality in southeastern Norway known for its rich Viking-age heritage and distinctive cultural traditions.
-
C.
Leikanger
Leikanger is a village and former municipality in Vestland county, Norway, situated along the Sognefjord and known for its fruit farming and scenic fjord landscape.
-
D.
Høyanger
Høyanger is a small industrial village and municipality in Vestland county, western Norway, known for its hydropower-based aluminum production and dramatic fjord landscape.
-
E.
Nissedal
Nissedal is a rural municipality in Vestfold og Telemark county, Norway, known for its forests, lakes, and outdoor recreation opportunities.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8dd0ad9088190a173b32657ae2e7a |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5f8a8daac8190b3558a1388596fb0 |
completed | April 20, 2026, 9:58 a.m. |
Created at: April 10, 2026, 12:07 p.m.