Triple
T14501513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gausdal |
E359649
|
entity |
| Predicate | hasAttraction |
P105
|
FINISHED |
| Object | Aulestad |
E542540
|
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: Aulestad | Statement: [Gausdal, hasAttraction, Aulestad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aulestad Context triple: [Gausdal, hasAttraction, Aulestad]
-
A.
Aulestad
chosen
Aulestad is the historic Norwegian country estate and museum best known as the longtime home of Nobel Prize–winning writer Bjørnstjerne Bjørnson.
-
B.
Gangstad
Gangstad is a small settlement located within the municipality of Inderøy in Trøndelag county, Norway.
-
C.
Grebbestad
Grebbestad is a coastal fishing village and popular tourist destination in Tanum Municipality on Sweden’s west coast, known for its seafood and picturesque archipelago.
-
D.
Svarstad
Svarstad is a Norwegian surname associated with individuals such as Maren Svarstad.
-
E.
Aursunden
Aursunden is a large lake in Røros municipality in Trøndelag county, Norway, known for its scenic surroundings and role in regional hydrology.
- 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de94dfe484819086dd971606e6478e |
completed | April 14, 2026, 7:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6d9b6f7481908b7eb76226a93545 |
completed | May 8, 2026, 4:59 a.m. |
Created at: April 10, 2026, 1:21 a.m.