Triple
T13541589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jan de Bont |
E323397
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Monique van de Ven |
E915208
|
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: Monique van de Ven | Statement: [Jan de Bont, spouse, Monique van de Ven]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Monique van de Ven Context triple: [Jan de Bont, spouse, Monique van de Ven]
-
A.
Monique van de Ven
chosen
Monique van de Ven is a prominent Dutch actress and director known for her leading roles in influential Dutch films such as "Turkish Delight" and "The Assault."
-
B.
Monique Peer
Monique Peer is known as the spouse of influential American music producer and talent scout Ralph Peer.
-
C.
Astrid Nienhuis
Astrid Nienhuis is a Dutch politician who serves as the mayor of the municipality of Heemstede in the Netherlands.
-
D.
Maria van den Boogaard
Maria van den Boogaard was the wife of Dutch politician and former Prime Minister Louis Beel.
-
E.
Johanna ter Steege
Johanna ter Steege is a Dutch actress acclaimed for her powerful performances in European cinema and international films.
- 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_69d8076776248190bdf0d4fa1f85a5fc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafd8ba10819098faadcc6adf251e |
completed | April 12, 2026, 2:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f76bae316081909e048ead31a9575a |
completed | May 3, 2026, 3:37 p.m. |
Created at: April 9, 2026, 9:45 p.m.