Triple
T23231469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sivert |
E581166
|
entity |
| Predicate | workOriginalTitle |
P13516
|
FINISHED |
| Object | Markens Grøde |
—
|
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: Markens Grøde | Statement: [Sivert, workOriginalTitle, Markens Grøde]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Markens Grøde Context triple: [Sivert, workOriginalTitle, Markens Grøde]
-
A.
Markens Grøde
chosen
Markens Grøde is a classic Norwegian novel by Knut Hamsun that portrays the struggles and rewards of pioneering rural life and the bond between humans and the land.
-
B.
Vårgrønn
Vårgrønn is a renewable energy company focused on developing offshore wind projects, particularly in the North Sea region.
-
C.
Grunert
Grunert is a German-origin surname borne by various notable individuals, including military figures and professionals in diverse fields.
-
D.
Rosendahl
Rosendahl is a municipality in the German state of North Rhine-Westphalia, known for its rural character and historic churches and castles.
-
E.
Borregaard
Borregaard is a Norwegian biorefinery company that produces advanced and sustainable bio-based chemicals and materials from wood.
- 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_69e246043c48819089bae72c9a9c306c |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f1923325a08190a529da687de53489 |
completed | April 29, 2026, 5:08 a.m. |
Created at: April 17, 2026, 4:09 p.m.