Triple
T12033193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kennemerland |
E286462
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Santpoort
Santpoort is a village in the Dutch province of North Holland, known for its historic estates, dunes, and proximity to the city of Haarlem.
|
E963812
|
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: Santpoort | Statement: [Kennemerland, contains, Santpoort]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santpoort Context triple: [Kennemerland, contains, Santpoort]
-
A.
Kaatsheuvel
Kaatsheuvel is a Dutch village best known as the home of the Efteling theme park, one of Europe’s largest and oldest amusement parks.
-
B.
Blokhuispoort
Blokhuispoort is a former prison complex in Leeuwarden, Netherlands, that has been transformed into a cultural and creative hub with museums, studios, and public spaces.
-
C.
Numansdorp
Numansdorp is a village in the western Netherlands known for its rural character and location on the island of Hoeksche Waard.
-
D.
Koepoort
Koepoort is a historic Dutch city gate known as one of the traditional entrances to a fortified town in the Netherlands.
-
E.
Bezuidenhout
Bezuidenhout is a neighborhood in The Hague, Netherlands, known for its residential character and proximity to major government and business districts.
- 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: Santpoort Triple: [Kennemerland, contains, Santpoort]
Generated description
Santpoort is a village in the Dutch province of North Holland, known for its historic estates, dunes, and proximity to the city of Haarlem.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Santpoort Target entity description: Santpoort is a village in the Dutch province of North Holland, known for its historic estates, dunes, and proximity to the city of Haarlem.
-
A.
Kaatsheuvel
Kaatsheuvel is a Dutch village best known as the home of the Efteling theme park, one of Europe’s largest and oldest amusement parks.
-
B.
Blokhuispoort
Blokhuispoort is a former prison complex in Leeuwarden, Netherlands, that has been transformed into a cultural and creative hub with museums, studios, and public spaces.
-
C.
Numansdorp
Numansdorp is a village in the western Netherlands known for its rural character and location on the island of Hoeksche Waard.
-
D.
Koepoort
Koepoort is a historic Dutch city gate known as one of the traditional entrances to a fortified town in the Netherlands.
-
E.
Bezuidenhout
Bezuidenhout is a neighborhood in The Hague, Netherlands, known for its residential character and proximity to major government and business districts.
- 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_69d6ab4669e48190b59246358b0383ab |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9040724ec8190808f334013ddc6d6 |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f646423c819088575a7032e6a9a3 |
completed | May 2, 2026, 1:04 p.m. |
| NEDg | Description generation | batch_69f5fed2d57881908103ce89a365cdd4 |
completed | May 2, 2026, 1:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f600bcaf288190b6204f985d3be638 |
completed | May 2, 2026, 1:48 p.m. |
Created at: April 8, 2026, 9:47 p.m.