Triple
T21993432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goede tijden, slechte tijden |
E543144
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object |
Noud Alberts
Noud Alberts is a fictional character from the long-running Dutch soap opera "Goede tijden, slechte tijden."
|
E1515368
|
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: Noud Alberts | Statement: [Goede tijden, slechte tijden, hasCharacter, Noud Alberts]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Noud Alberts Context triple: [Goede tijden, slechte tijden, hasCharacter, Noud Alberts]
-
A.
Benno de Goeij
Benno de Goeij is a Dutch trance music producer and songwriter best known for his work with Armin van Buuren and as part of influential projects like Rank 1.
-
B.
Jan van der Meer
Jan van der Meer is a personal name shared by multiple individuals, typically of Dutch origin, rather than a single widely recognized public figure.
-
C.
Johan de Jonge
Johan de Jonge is a person notable enough to be recognized as a distinguished bearer of the surname "de Jonge."
-
D.
Dirk Margadant
Dirk Margadant was a Dutch architect known for designing prominent public buildings in the Netherlands, including notable railway stations.
-
E.
Hubert Bruls
Hubert Bruls is a Dutch politician best known as the long-serving mayor of Nijmegen and a prominent figure in national public safety and crisis management.
- 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: Noud Alberts Triple: [Goede tijden, slechte tijden, hasCharacter, Noud Alberts]
Generated description
Noud Alberts is a fictional character from the long-running Dutch soap opera "Goede tijden, slechte tijden."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Noud Alberts Target entity description: Noud Alberts is a fictional character from the long-running Dutch soap opera "Goede tijden, slechte tijden."
-
A.
Benno de Goeij
Benno de Goeij is a Dutch trance music producer and songwriter best known for his work with Armin van Buuren and as part of influential projects like Rank 1.
-
B.
Jan van der Meer
Jan van der Meer is a personal name shared by multiple individuals, typically of Dutch origin, rather than a single widely recognized public figure.
-
C.
Johan de Jonge
Johan de Jonge is a person notable enough to be recognized as a distinguished bearer of the surname "de Jonge."
-
D.
Dirk Margadant
Dirk Margadant was a Dutch architect known for designing prominent public buildings in the Netherlands, including notable railway stations.
-
E.
Hubert Bruls
Hubert Bruls is a Dutch politician best known as the long-serving mayor of Nijmegen and a prominent figure in national public safety and crisis management.
- 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_69e11e2c814c8190837d072789000486 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1270f77fc8190aadcc02760d65ac0 |
completed | April 28, 2026, 9:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0a7b5e56588190bd9be43375ecb86a |
completed | May 18, 2026, 2:37 a.m. |
| NEDg | Description generation | batch_6a0a7c73537481908c644642f825569f |
completed | May 18, 2026, 2:41 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0a7d29f5a08190b41cad11e2192727 |
completed | May 18, 2026, 2:44 a.m. |
Created at: April 16, 2026, 8:17 p.m.