Triple
T23508482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kees van Kooten |
E572350
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | van Kooten |
—
|
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: van Kooten | Statement: [Kees van Kooten, familyName, van Kooten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: van Kooten Context triple: [Kees van Kooten, familyName, van Kooten]
-
A.
van Heiden
Van Heiden is a Dutch surname most notably associated with Admiral Lodewijk van Heiden, a distinguished naval officer in Russian service during the early 19th century.
-
B.
van Wijnbergen
Van Wijnbergen is a Dutch surname associated with individuals such as Everdine Huberta van Wijnbergen.
-
C.
Kees van Kooten
chosen
Kees van Kooten is a Dutch writer, satirist, and comedian known for his influential work in literature and television, often created in collaboration with Wim de Bie.
-
D.
Kwade Hoek
Kwade Hoek is a coastal nature reserve in the Netherlands known for its salt marshes, dunes, and rich birdlife.
-
E.
Van der Madeweg
Van der Madeweg is a metro station in Amsterdam that serves as a stop on the city's rapid transit network.
- 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_69e245b5e4208190bac8a6509867e394 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a902c0788190840d7df1b5450b4d |
completed | April 29, 2026, 6:45 a.m. |
Created at: April 17, 2026, 6:07 p.m.