Triple
T4790510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orkland |
E106588
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Orkanger |
E507899
|
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: Orkanger | Statement: [Orkland, hasSettlement, Orkanger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orkanger Context triple: [Orkland, hasSettlement, 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.
Gaustad
Gaustad is a district in Oslo, Norway, known for hosting major academic and research institutions, including parts of the University of Oslo campus.
-
D.
Kragerø
Kragerø is a coastal town in Norway renowned for its picturesque archipelago, historic wooden buildings, and role as a popular summer holiday destination.
-
E.
Alstahaug
Alstahaug is a coastal municipality in northern Norway known for its historic church, island landscapes, and maritime heritage.
- 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_69bd43f591c881909e5a532388b0f3f3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd65dce6888190a0b1bdf416fb62b9 |
completed | March 20, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf185bce7c8190ad94ab3f848a0040 |
completed | March 21, 2026, 10:14 p.m. |
Created at: March 20, 2026, 1:22 p.m.