Triple
T6359451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jay Bouwmeester |
E143072
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Bouwmeester
Bouwmeester is a Dutch-origin surname borne by various notable individuals, including professional ice hockey player Jay Bouwmeester.
|
E587533
|
NE FINISHED |
How this triple was built (4 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: Bouwmeester | Statement: [Jay Bouwmeester, familyName, Bouwmeester]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bouwmeester Context triple: [Jay Bouwmeester, familyName, Bouwmeester]
-
A.
Sjaalman
Sjaalman is a fictional character in Multatuli’s novel "Max Havelaar," serving as an alter ego and narrative device to expose colonial abuses in the Dutch East Indies.
-
B.
Theo de Meester
Theo de Meester was a Dutch liberal politician who served as Prime Minister of the Netherlands in the early 20th century.
-
C.
Molenaar
Molenaar is a Dutch occupational surname meaning "miller," referring to someone who operates or works at a mill.
-
D.
Yorick van Wageningen
Yorick van Wageningen is a Dutch actor known internationally for his roles in films such as the 2011 adaptation of "The Girl with the Dragon Tattoo."
-
E.
Aeltge Velthuys
Aeltge Velthuys was the wife of Dutch Golden Age painter Carel Fabritius, known primarily through her connection to the artist.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Bouwmeester Triple: [Jay Bouwmeester, familyName, Bouwmeester]
Generated description
Bouwmeester is a Dutch-origin surname borne by various notable individuals, including professional ice hockey player Jay Bouwmeester.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bouwmeester Target entity description: Bouwmeester is a Dutch-origin surname borne by various notable individuals, including professional ice hockey player Jay Bouwmeester.
-
A.
Sjaalman
Sjaalman is a fictional character in Multatuli’s novel "Max Havelaar," serving as an alter ego and narrative device to expose colonial abuses in the Dutch East Indies.
-
B.
Theo de Meester
Theo de Meester was a Dutch liberal politician who served as Prime Minister of the Netherlands in the early 20th century.
-
C.
Molenaar
Molenaar is a Dutch occupational surname meaning "miller," referring to someone who operates or works at a mill.
-
D.
Yorick van Wageningen
Yorick van Wageningen is a Dutch actor known internationally for his roles in films such as the 2011 adaptation of "The Girl with the Dragon Tattoo."
-
E.
Aeltge Velthuys
Aeltge Velthuys was the wife of Dutch Golden Age painter Carel Fabritius, known primarily through her connection to the artist.
- F. None of above. chosen
Provenance (5 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_69c008d7a9c4819098d647ec47776917 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c067f72f8481908f9df0c0cdf22a52 |
completed | March 22, 2026, 10:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c62d66a8a08190b52bb8302787dac5 |
completed | March 27, 2026, 7:10 a.m. |
| NEDg | Description generation | batch_69c62e430ac08190bacf74f6086b2ac5 |
completed | March 27, 2026, 7:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c62f03ea408190a0959b8f2aa746c1 |
completed | March 27, 2026, 7:17 a.m. |
Created at: March 22, 2026, 4:32 p.m.