Triple
T10695778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holland |
E252134
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object |
van Holland
Van Holland is a variant form of the name Holland, typically used as a Dutch surname indicating origin from the Holland region of the Netherlands.
|
E880725
|
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: van Holland | Statement: [Holland, hasVariant, van Holland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: van Holland Context triple: [Holland, hasVariant, van Holland]
-
A.
Hollander
Hollander is a surname most prominently associated with English actor Tom Hollander, known for his versatile roles in film, television, and theatre.
-
B.
van Slingelandt
Van Slingelandt is a Dutch surname historically associated with a prominent political and administrative family in the Netherlands.
-
C.
van Dam
van Dam is a Dutch surname commonly associated with individuals of Dutch origin or ancestry.
-
D.
van Wassenaer
van Wassenaer is a Dutch noble family name historically associated with prominent military and political figures in the Netherlands.
-
E.
Van der Madeweg
Van der Madeweg is a metro station in Amsterdam that serves as a stop on the city's rapid transit 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: van Holland Triple: [Holland, hasVariant, van Holland]
Generated description
Van Holland is a variant form of the name Holland, typically used as a Dutch surname indicating origin from the Holland region of the Netherlands.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: van Holland Target entity description: Van Holland is a variant form of the name Holland, typically used as a Dutch surname indicating origin from the Holland region of the Netherlands.
-
A.
Hollander
Hollander is a surname most prominently associated with English actor Tom Hollander, known for his versatile roles in film, television, and theatre.
-
B.
van Slingelandt
Van Slingelandt is a Dutch surname historically associated with a prominent political and administrative family in the Netherlands.
-
C.
van Dam
van Dam is a Dutch surname commonly associated with individuals of Dutch origin or ancestry.
-
D.
van Wassenaer
van Wassenaer is a Dutch noble family name historically associated with prominent military and political figures in the Netherlands.
-
E.
Van der Madeweg
Van der Madeweg is a metro station in Amsterdam that serves as a stop on the city's rapid transit 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_69d6aa5bd7c08190a816e733b4045c23 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fd3af5248190ab807965255e9ad2 |
completed | April 9, 2026, 1:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d998da1738819099a9090c3e8badc9 |
completed | April 11, 2026, 12:42 a.m. |
| NEDg | Description generation | batch_69d99e8534688190b312b737e0b9cd53 |
completed | April 11, 2026, 1:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69dadcb861a08190bb9f64a91117f35d |
completed | April 11, 2026, 11:43 p.m. |
Created at: April 8, 2026, 9:11 p.m.