Triple
T7668363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hendrik van der Meer |
E173681
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | van der Meer |
E173681
|
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: van der Meer | Statement: [Hendrik van der Meer, familyName, van der Meer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: van der Meer Context triple: [Hendrik van der Meer, familyName, van der Meer]
-
A.
van der Meer
chosen
Van der Meer is a Dutch surname borne by several notable individuals, including Nobel Prize–winning physicist Simon van der Meer.
-
B.
van Wijnbergen
Van Wijnbergen is a Dutch surname associated with individuals such as Everdine Huberta van Wijnbergen.
-
C.
van de Velde
Van de Velde is a Dutch surname borne by several notable figures, including artists, designers, and writers from the Low Countries.
-
D.
Johannes van der Meer
Johannes van der Meer is another name for Johannes Vermeer, the renowned 17th-century Dutch painter celebrated for his masterful use of light and intimate domestic interior scenes.
-
E.
van Slingelandt
Van Slingelandt is a Dutch surname historically associated with a prominent political and administrative family 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_69c699562484819086752091e3164a27 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c701c3ff38819090d65ac4ae218750 |
completed | March 27, 2026, 10:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8b4f716a48190a0ca52caffc2c1c1 |
completed | March 29, 2026, 5:13 a.m. |
Created at: March 27, 2026, 4 p.m.