Triple
T8785858
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | i/o |
E209040
|
entity |
| Predicate | coverArtDesigner |
P184
|
FINISHED |
| Object | Ane Brun |
E355249
|
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: Ane Brun | Statement: [i/o, coverArtDesigner, Ane Brun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ane Brun Context triple: [i/o, coverArtDesigner, Ane Brun]
-
A.
Ane Brun
chosen
Ane Brun is a Norwegian singer-songwriter known for her introspective folk-pop music and distinctive, emotive vocal style.
-
B.
Maren Svarstad
Maren Svarstad was a daughter of the Norwegian Nobel Prize–winning author Sigrid Undset.
-
C.
Anna Sofie Bergen
Anna Sofie Bergen was the mother of composer and cultural figure Alma Mahler, belonging to the milieu of late 19th-century Viennese artistic society.
-
D.
Sandi Sissel
Sandi Sissel is an American cinematographer and documentary filmmaker known for her work on both narrative features and non-fiction films.
-
E.
Synnøve Solbakken
Synnøve Solbakken is a 1857 Norwegian peasant novel by Bjørnstjerne Bjørnson that portrays rural life and moral ideals through the love story of a young couple.
- 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_69ca836168108190bb43d3dc235c1f55 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f758d348190804942d985f2337c |
completed | March 31, 2026, 11:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf51fded4c81909725807e4855c4a2 |
completed | April 3, 2026, 5:37 a.m. |
Created at: March 30, 2026, 6:42 p.m.