Triple
T9720968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rijk de Gooyer |
E235468
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
In voor- en tegenspoed
In voor- en tegenspoed is a Dutch television series best known as a popular sitcom featuring Rijk de Gooyer in a leading role.
|
E816420
|
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: In voor- en tegenspoed | Statement: [Rijk de Gooyer, notableWork, In voor- en tegenspoed]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: In voor- en tegenspoed Context triple: [Rijk de Gooyer, notableWork, In voor- en tegenspoed]
-
A.
Voorschoten
Voorschoten is a town and municipality in the western Netherlands, situated between The Hague and Leiden and known for its residential character and historic village center.
-
B.
Driewegen
Driewegen is a small village in the Dutch province of Zeeland, located within the municipality of Borsele.
-
C.
Eendragt maakt magt
"Eendragt maakt magt" is a historic Dutch motto meaning "Unity makes strength," prominently associated with the South African Republic.
-
D.
Achtmaal
Achtmaal is a small village in the municipality of Zundert in the Dutch province of North Brabant.
-
E.
Spijkenisse
Spijkenisse is a town and former municipality in the western Netherlands, now part of the municipality of Nissewaard and known as a suburban area near Rotterdam.
- 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: In voor- en tegenspoed Triple: [Rijk de Gooyer, notableWork, In voor- en tegenspoed]
Generated description
In voor- en tegenspoed is a Dutch television series best known as a popular sitcom featuring Rijk de Gooyer in a leading role.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: In voor- en tegenspoed Target entity description: In voor- en tegenspoed is a Dutch television series best known as a popular sitcom featuring Rijk de Gooyer in a leading role.
-
A.
Voorschoten
Voorschoten is a town and municipality in the western Netherlands, situated between The Hague and Leiden and known for its residential character and historic village center.
-
B.
Driewegen
Driewegen is a small village in the Dutch province of Zeeland, located within the municipality of Borsele.
-
C.
Eendragt maakt magt
"Eendragt maakt magt" is a historic Dutch motto meaning "Unity makes strength," prominently associated with the South African Republic.
-
D.
Achtmaal
Achtmaal is a small village in the municipality of Zundert in the Dutch province of North Brabant.
-
E.
Spijkenisse
Spijkenisse is a town and former municipality in the western Netherlands, now part of the municipality of Nissewaard and known as a suburban area near Rotterdam.
- 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_69ca84d0123c819096f9dc3b6abb0881 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9e419c2c8190b325d5fd692c6000 |
completed | April 1, 2026, 10:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d19fa130548190ae729487b90fa8a7 |
completed | April 4, 2026, 11:32 p.m. |
| NEDg | Description generation | batch_69d1a0b4dbf8819097e38c253327fc10 |
completed | April 4, 2026, 11:37 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1a172ad848190a76f95c4937689d7 |
completed | April 4, 2026, 11:40 p.m. |
Created at: March 30, 2026, 8:20 p.m.