Triple
T10245249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Afrojack |
E240196
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object | Nick van de Wall |
E240196
|
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: Nick van de Wall | Statement: [Afrojack, birthName, Nick van de Wall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nick van de Wall Context triple: [Afrojack, birthName, Nick van de Wall]
-
A.
Nick van de Wall
chosen
Nick van de Wall, better known as Afrojack, is a Dutch DJ and record producer recognized as one of the leading figures in contemporary electronic dance music.
-
B.
Tim Kruithoff
Tim Kruithoff is a German local politician who serves as the mayor of the city of Emden in Lower Saxony.
-
C.
Sander van Doorn
Sander van Doorn is a Dutch DJ and electronic music producer known for his influential work in trance and progressive house.
-
D.
Martin Dekker
Martin Dekker is a fictional character appearing in the Doctor Who audio drama "The Silence."
-
E.
Christian Huitema
Christian Huitema is a French computer scientist and Internet pioneer known for his influential work on networking protocols and IPv6 transition technologies.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d22be0208190b671a4e3f81d11b8 |
completed | April 7, 2026, 9:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f79c20e08190928d061b3d4b4e47 |
completed | April 9, 2026, 12:49 a.m. |
Created at: April 6, 2026, 11:26 a.m.