Triple
T13065615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryfylke |
E329313
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Haugalandet |
E382170
|
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: Haugalandet | Statement: [Ryfylke, borders, Haugalandet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haugalandet Context triple: [Ryfylke, borders, Haugalandet]
-
A.
Haugalandet
chosen
Haugalandet is a coastal region in western Norway centered around the town of Haugesund, known for its maritime heritage and North Sea industries.
-
B.
Hadeland
Hadeland is a traditional rural district in southeastern Norway known for its agricultural landscape, historic churches, and the Hadeland Glassverk glassworks.
-
C.
Ottosdal
Ottosdal is a small agricultural town in South Africa’s North West province, known for its grain farming and rural character.
-
D.
Nadderud
Nadderud is a residential and sports-focused area in Bærum, Norway, known for its stadium and athletic facilities.
-
E.
Suldal
Suldal is a large rural municipality in southwestern Norway known for its fjords, mountains, and hydroelectric power production.
- 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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980eb81948190b27eb9ae19978079 |
completed | April 10, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ff051bc88190a55c55377a352d3b |
completed | May 3, 2026, 7:53 a.m. |
Created at: April 9, 2026, 8:59 p.m.