Triple
T15280549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koos Vorrink |
E365256
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Koos |
E42621
|
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: Koos | Statement: [Koos Vorrink, givenName, Koos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Koos Context triple: [Koos Vorrink, givenName, Koos]
-
A.
Koos
chosen
Koos is the commonly used nickname of Koos de la Rey, a prominent Boer general and political figure from South African history.
-
B.
Kolderbos
Kolderbos is a residential district of the Belgian city of Genk, known for its post-war social housing and multicultural community.
-
C.
Voskuijl
Voskuijl is a Dutch surname most notably associated with Bep Voskuijl, one of the helpers of Anne Frank and her family during their time in hiding.
-
D.
Vriezekoop
Vriezekoop is a small village in the Dutch province of South Holland, known for its rural character and location along the Westeinderplassen near Leimuiden.
-
E.
Koekamp
Koekamp is a historic green park and deer reserve on the edge of central The Hague in the Netherlands.
- 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_69d85a103d9081908c1ea6c4c73ac8e3 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e00e504d8c8190ad6c565a31d1a9bd |
completed | April 15, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feef754c9c8190abdc1d08fd1511cd |
completed | May 9, 2026, 8:25 a.m. |
Created at: April 10, 2026, 3:15 a.m.