Triple
T5933077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Multatuli Prize |
E131981
|
entity |
| Predicate | hasAwarded |
P2391
|
FINISHED |
| Object |
Oek de Jong
Oek de Jong is a Dutch novelist known for his psychologically rich, stylistically refined prose and significant influence on contemporary Dutch literature.
|
E555190
|
NE FINISHED |
How this triple was built (4 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: Oek de Jong | Statement: [Multatuli Prize, hasAwarded, Oek de Jong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oek de Jong Context triple: [Multatuli Prize, hasAwarded, Oek de Jong]
-
A.
de Jonge
De Jonge is a Dutch surname borne by various notable figures, including politicians, artists, and athletes in the Netherlands.
-
B.
Sjoukje
Sjoukje is a feminine given name of Dutch origin, commonly used in the Netherlands and Friesland.
-
C.
Leen
Leen is the name of a river in Nottinghamshire, England, known as the River Leen, which flows through the city of Nottingham before joining the River Trent.
-
D.
Ineke Hans
Ineke Hans is a Dutch industrial designer known for her innovative furniture and product designs that blend functionality with playful, conceptual aesthetics.
-
E.
Jan D'Alquen
Jan D'Alquen is a cinematographer best known for his work on the classic coming-of-age film "American Graffiti."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Oek de Jong Triple: [Multatuli Prize, hasAwarded, Oek de Jong]
Generated description
Oek de Jong is a Dutch novelist known for his psychologically rich, stylistically refined prose and significant influence on contemporary Dutch literature.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Oek de Jong Target entity description: Oek de Jong is a Dutch novelist known for his psychologically rich, stylistically refined prose and significant influence on contemporary Dutch literature.
-
A.
de Jonge
De Jonge is a Dutch surname borne by various notable figures, including politicians, artists, and athletes in the Netherlands.
-
B.
Sjoukje
Sjoukje is a feminine given name of Dutch origin, commonly used in the Netherlands and Friesland.
-
C.
Leen
Leen is the name of a river in Nottinghamshire, England, known as the River Leen, which flows through the city of Nottingham before joining the River Trent.
-
D.
Ineke Hans
Ineke Hans is a Dutch industrial designer known for her innovative furniture and product designs that blend functionality with playful, conceptual aesthetics.
-
E.
Jan D'Alquen
Jan D'Alquen is a cinematographer best known for his work on the classic coming-of-age film "American Graffiti."
- F. None of above. chosen
Provenance (5 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_69c0085c55dc8190aa90e242c956e2fa |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0389f6fc881909527b928838ffcdd |
completed | March 22, 2026, 6:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0c064d2a4819096085668182cfde1 |
completed | March 23, 2026, 4:24 a.m. |
| NEDg | Description generation | batch_69c0c109b3288190928dc4539a2872c2 |
completed | March 23, 2026, 4:26 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0c1f6fe60819080a00976740b6a9c |
completed | March 23, 2026, 4:30 a.m. |
Created at: March 22, 2026, 4 p.m.