Triple
T13065598
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ryfylke |
E329313
|
entity |
| Predicate | hasTouristAttraction |
P530
|
FINISHED |
| Object | Preikestolen |
E365816
|
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: Preikestolen | Statement: [Ryfylke, hasTouristAttraction, Preikestolen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Preikestolen Context triple: [Ryfylke, hasTouristAttraction, Preikestolen]
-
A.
Preikestolen
chosen
Preikestolen is a famous steep cliff and viewpoint in southwestern Norway that towers over the Lysefjord and attracts many hikers and tourists.
-
B.
Slottsfjellet
Slottsfjellet is a historic hill and former fortress site in Tønsberg, Norway, known for its medieval castle ruins and prominent tower overlooking the city.
-
C.
Kolåstinden
Kolåstinden is a prominent alpine peak in Norway’s Sunnmøre Alps, renowned among hikers and ski mountaineers for its steep slopes and panoramic fjord views.
-
D.
Kjerkeberget
Kjerkeberget is a forested hill in Norway that marks the highest natural point within Oslo’s municipal boundaries.
-
E.
Avaldsnes
Avaldsnes is a historic village in Rogaland county, Norway, known as one of the country’s oldest royal seats and a key center in Viking-era history.
- 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_69f6cbe630808190a9a3481127bbaa86 |
completed | May 3, 2026, 4:15 a.m. |
Created at: April 9, 2026, 8:59 p.m.