Triple
T23448467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Everdine Huberta van Wijnbergen |
E565607
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | van Wijnbergen |
—
|
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 Wijnbergen | Statement: [Everdine Huberta van Wijnbergen, familyName, van Wijnbergen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: van Wijnbergen Context triple: [Everdine Huberta van Wijnbergen, familyName, van Wijnbergen]
-
A.
van Wijnbergen
chosen
Van Wijnbergen is a Dutch surname associated with individuals such as Everdine Huberta van Wijnbergen.
-
B.
van Slingelandt
Van Slingelandt is a Dutch surname historically associated with a prominent political and administrative family in the Netherlands.
-
C.
Jan van Wijk
Jan van Wijk was a South African architect best known for designing the iconic Afrikaans Language Monument in Paarl.
-
D.
van Hoften
Van Hoften is the surname of James D. van Hoften, an American former NASA astronaut and aerospace engineer.
-
E.
van Swanenburg
Van Swanenburg is a Dutch family name historically associated with artists and notable figures from the Netherlands.
- 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_69e24584f9488190bb32730bd2ce023e |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1a64b27988190b4722425da964407 |
completed | April 29, 2026, 6:33 a.m. |
Created at: April 17, 2026, 5:52 p.m.