Triple
T23374324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Derek de Lint |
E593563
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
De Fabriek
De Fabriek is a Dutch film best known for featuring actor Derek de Lint in a prominent role.
|
E1583909
|
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: De Fabriek | Statement: [Derek de Lint, notableWork, De Fabriek]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: De Fabriek Context triple: [Derek de Lint, notableWork, De Fabriek]
-
A.
De Dokwerker
De Dokwerker is a bronze statue in Amsterdam commemorating the February Strike of 1941 and symbolizing resistance against Nazi persecution.
-
B.
Het Posthuys
Het Posthuys is one of the oldest surviving buildings in Muizenberg, South Africa, historically used as a post house and lookout during the early colonial period.
-
C.
La Fabrique
La Fabrique is a contemporary cultural and creative arts hub on the Île de Nantes in France, known for hosting concerts, exhibitions, and innovative artistic projects.
-
D.
Maan de Steenwinkel
Maan de Steenwinkel is a Dutch singer and actress who rose to fame after winning the talent show The Voice of Holland and has since built a successful pop music career.
-
E.
De Akkers
De Akkers is a metro station in Spijkenisse, Netherlands, serving as a terminus on the Rotterdam Metro network.
- 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: De Fabriek Triple: [Derek de Lint, notableWork, De Fabriek]
Generated description
De Fabriek is a Dutch film best known for featuring actor Derek de Lint in a prominent role.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: De Fabriek Target entity description: De Fabriek is a Dutch film best known for featuring actor Derek de Lint in a prominent role.
-
A.
De Dokwerker
De Dokwerker is a bronze statue in Amsterdam commemorating the February Strike of 1941 and symbolizing resistance against Nazi persecution.
-
B.
Het Posthuys
Het Posthuys is one of the oldest surviving buildings in Muizenberg, South Africa, historically used as a post house and lookout during the early colonial period.
-
C.
La Fabrique
La Fabrique is a contemporary cultural and creative arts hub on the Île de Nantes in France, known for hosting concerts, exhibitions, and innovative artistic projects.
-
D.
Maan de Steenwinkel
Maan de Steenwinkel is a Dutch singer and actress who rose to fame after winning the talent show The Voice of Holland and has since built a successful pop music career.
-
E.
De Akkers
De Akkers is a metro station in Spijkenisse, Netherlands, serving as a terminus on the Rotterdam Metro network.
- 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_69e25d268a50819095f2fd479da8ef3f |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a3b1d24881909945936cbf00876e |
completed | April 29, 2026, 6:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c5ddfbbf0819098166b60f5e5e62e |
completed | May 19, 2026, 12:55 p.m. |
| NEDg | Description generation | batch_6a0c5fc2cd908190b86c0f915db3a1e3 |
completed | May 19, 2026, 1:04 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c603b3ad08190b9bfead27448fc58 |
completed | May 19, 2026, 1:06 p.m. |
Created at: April 17, 2026, 5:33 p.m.