Triple
T662342
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Håkons Hall |
E11782
|
entity |
| Predicate | locatedInAdministrativeTerritory |
P40
|
FINISHED |
| Object | Oppland |
E65743
|
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: Oppland | Statement: [Håkons Hall, locatedInAdministrativeTerritory, Oppland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oppland Context triple: [Håkons Hall, locatedInAdministrativeTerritory, Oppland]
-
A.
Trøndelag
Trøndelag is a central region of Norway known for its historic city of Trondheim, coastal landscapes, and strong cultural traditions.
-
B.
Aust-Agder
Aust-Agder was a former county in southern Norway known for its coastal towns, forests, and role in the country’s maritime and timber industries.
-
C.
Troms og Finnmark
Troms og Finnmark is Norway’s northernmost and largest county, known for its Arctic landscapes, Sami culture, and phenomena like the midnight sun and northern lights.
-
D.
Nordland
Nordland is a long coastal county in northern Norway known for its dramatic fjords, islands like the Lofoten archipelago, and Arctic landscapes.
-
E.
Oppland (former county)
chosen
Oppland was a former inland county in eastern Norway known for its mountainous terrain, ski resorts, and important winter sports venues.
- 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_69a4932862a0819098be659c814e4981 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49fd081e8819097f289961f5eff29 |
completed | March 1, 2026, 8:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5dc98e43881909fbc74750f4b6e3b |
completed | March 2, 2026, 6:53 p.m. |
Created at: March 1, 2026, 7:36 p.m.