Triple
T20628640
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ivar Aasen |
E506888
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Ivar Aasen |
—
|
NE NERFINISHED |
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: Ivar Aasen | Statement: [Ivar Aasen, name, Ivar Aasen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ivar Aasen Context triple: [Ivar Aasen, name, Ivar Aasen]
-
A.
Ivar Aasen
chosen
Ivar Aasen was a Norwegian philologist, lexicographer, and poet best known for creating Nynorsk, one of the two official written standards of the Norwegian language.
-
B.
Johan Ernst Gunnerus
Johan Ernst Gunnerus was an 18th-century Norwegian bishop and naturalist renowned for his pioneering contributions to botany and for co-founding the Royal Norwegian Society of Sciences and Letters.
-
C.
Erling Bjørnson
Erling Bjørnson was a Norwegian farmer and politician, best known as the son of Nobel Prize–winning writer Bjørnstjerne Bjørnson.
-
D.
Eilif Skodvin
Eilif Skodvin is a Norwegian screenwriter and television creator best known for co-creating the crime-comedy series "Lilyhammer."
-
E.
Eilif Peterssen
Eilif Peterssen was a prominent Norwegian painter of the late 19th and early 20th centuries, known for his portraits, historical scenes, and landscapes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4bd4a0081908d4e97a590a33fb2 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6abe771e88190a48471bf83b4804d |
completed | April 20, 2026, 10:42 p.m. |
Created at: April 16, 2026, 11:42 a.m.