Triple
T8279449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vår Frelsers gravlund |
E193632
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Oslo county |
E134025
|
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: Oslo county | Statement: [Vår Frelsers gravlund, locatedIn, Oslo county]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oslo county Context triple: [Vår Frelsers gravlund, locatedIn, Oslo county]
-
A.
Oslo county
chosen
Oslo county is Norway’s capital county, encompassing the city of Oslo and serving as the country’s political, economic, and cultural center.
-
B.
Akershus county
Akershus county was a former county in southeastern Norway that historically surrounded Oslo and included both urban suburbs and rural areas before being merged into Viken county.
-
C.
Hedmark
Hedmark is a former county in eastern Norway known for its vast forests, agriculture, and inland landscapes along the Swedish border.
-
D.
Hedmarken
Hedmarken is a traditional district in Innlandet county in eastern Norway, known for its agricultural landscapes and its central town, Hamar.
-
E.
Sogn og Fjordane
Sogn og Fjordane was a former county in western Norway known for its dramatic fjords, mountains, and coastal landscapes.
- 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_69ca82e217a48190880695635c44b2ed |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb79ece5708190a1569bcfad5b3644 |
completed | March 31, 2026, 7:38 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce4d8a7eb48190bc1bebc56a46a5b9 |
completed | April 2, 2026, 11:05 a.m. |
Created at: March 30, 2026, 5:51 p.m.