Triple
T22514969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viggo Widerøe |
E556617
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Viggo |
—
|
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: Viggo | Statement: [Viggo Widerøe, givenName, Viggo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Viggo Context triple: [Viggo Widerøe, givenName, Viggo]
-
A.
Viggo
chosen
Viggo is a Danish royal given name borne by Prince Viggo of Denmark, a 20th-century member of the Danish royal family.
-
B.
Frederick Valk
Frederick Valk was a German-born British character actor known for his powerful stage and film performances in mid-20th-century British cinema and theatre.
-
C.
Suvari
Suvari is the surname of American actress and model Mena Suvari, known for her roles in films like "American Beauty" and the "American Pie" series.
-
D.
Kristofer Hivju
Kristofer Hivju is a Norwegian actor best known internationally for his role as Tormund Giantsbane in the television series Game of Thrones.
-
E.
Michael Black
Michael Black is an individual member of the Black family, a lineage or household identified by the shared Black surname.
- 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_69e11e555edc81909ca803587dafd747 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15e2c3098819098a553133cc9515b |
completed | April 29, 2026, 1:26 a.m. |
Created at: April 16, 2026, 8:50 p.m.