Triple
T960193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amsterdam Sloterdijk |
E20717
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object |
Alkmaar
Alkmaar is a historic city in the Netherlands, renowned for its traditional cheese market and well-preserved medieval center.
|
E445674
|
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: Alkmaar | Statement: [Amsterdam Sloterdijk, connectsTo, Alkmaar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alkmaar Context triple: [Amsterdam Sloterdijk, connectsTo, Alkmaar]
-
A.
Almere
Almere is a modern planned city in the Dutch province of Flevoland, known for its rapid growth, contemporary architecture, and role as a major commuter town near Amsterdam.
-
B.
Gorinchem
Gorinchem is a historic fortified city in the Netherlands known for its well-preserved city walls and picturesque old town.
-
C.
Hellevoetsluis
Hellevoetsluis is a historic Dutch port town known for its maritime heritage and coastal location in the western Netherlands.
-
D.
Apeldoorn
Apeldoorn is a city in the province of Gelderland in the Netherlands, known for the royal palace Het Loo and its historical ties to the Dutch monarchy.
-
E.
Aalsmeer
Aalsmeer is a Dutch town in North Holland best known as a global center for the flower and plant trade, hosting one of the world’s largest flower auctions.
- 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: Alkmaar Triple: [Amsterdam Sloterdijk, connectsTo, Alkmaar]
Generated description
Alkmaar is a historic city in the Netherlands, renowned for its traditional cheese market and well-preserved medieval center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alkmaar Target entity description: Alkmaar is a historic city in the Netherlands, renowned for its traditional cheese market and well-preserved medieval center.
-
A.
Almere
Almere is a modern planned city in the Dutch province of Flevoland, known for its rapid growth, contemporary architecture, and role as a major commuter town near Amsterdam.
-
B.
Gorinchem
Gorinchem is a historic fortified city in the Netherlands known for its well-preserved city walls and picturesque old town.
-
C.
Hellevoetsluis
Hellevoetsluis is a historic Dutch port town known for its maritime heritage and coastal location in the western Netherlands.
-
D.
Apeldoorn
Apeldoorn is a city in the province of Gelderland in the Netherlands, known for the royal palace Het Loo and its historical ties to the Dutch monarchy.
-
E.
Aalsmeer
Aalsmeer is a Dutch town in North Holland best known as a global center for the flower and plant trade, hosting one of the world’s largest flower auctions.
- 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_69a493b21f2881908132dcf45dcd2f36 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b412f9f48190be123e8c20f38962 |
completed | March 1, 2026, 9:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bb60bff62881908ff53b9b02d9c869 |
completed | March 19, 2026, 2:34 a.m. |
| NEDg | Description generation | batch_69bb6841dd7881909e946d9965c8509c |
completed | March 19, 2026, 3:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bb68a42af4819089a6502187d6f22b |
completed | March 19, 2026, 3:08 a.m. |
Created at: March 1, 2026, 7:40 p.m.