Triple
T4041119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Velsen |
E83948
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object |
Beverwijk
Beverwijk is a town and municipality in North Holland, Netherlands, known for its large indoor market and proximity to the North Sea coast.
|
E807426
|
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: Beverwijk | Statement: [Velsen, borderedBy, Beverwijk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Beverwijk Context triple: [Velsen, borderedBy, Beverwijk]
-
A.
Oisterwijk
Oisterwijk is a town in the Dutch province of North Brabant known for its historic center and surrounding forest and fen landscapes.
-
B.
Meerwijk
Meerwijk is a residential neighborhood within the town of Uithoorn in the province of North Holland, Netherlands.
-
C.
Waalwijk
Waalwijk is a town and municipality in the southern Netherlands known historically for its leather and shoe industry.
-
D.
Leidschendam-Voorburg
Leidschendam-Voorburg is a municipality in the western Netherlands, near The Hague, formed by the towns of Leidschendam and Voorburg.
-
E.
Bernisse
Bernisse is a waterway in the South Holland province of the Netherlands, known for connecting several polders and serving as a recreational and natural area.
- 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: Beverwijk Triple: [Velsen, borderedBy, Beverwijk]
Generated description
Beverwijk is a town and municipality in North Holland, Netherlands, known for its large indoor market and proximity to the North Sea coast.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Beverwijk Target entity description: Beverwijk is a town and municipality in North Holland, Netherlands, known for its large indoor market and proximity to the North Sea coast.
-
A.
Oisterwijk
Oisterwijk is a town in the Dutch province of North Brabant known for its historic center and surrounding forest and fen landscapes.
-
B.
Meerwijk
Meerwijk is a residential neighborhood within the town of Uithoorn in the province of North Holland, Netherlands.
-
C.
Waalwijk
Waalwijk is a town and municipality in the southern Netherlands known historically for its leather and shoe industry.
-
D.
Leidschendam-Voorburg
Leidschendam-Voorburg is a municipality in the western Netherlands, near The Hague, formed by the towns of Leidschendam and Voorburg.
-
E.
Bernisse
Bernisse is a waterway in the South Holland province of the Netherlands, known for connecting several polders and serving as a recreational and natural area.
- 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_69aed92f7cf0819098e0539bdcc3767f |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb3a9314819095dcf47675eedb48 |
completed | March 9, 2026, 4:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1524be8c08190b4d979a677dc5958 |
completed | April 4, 2026, 6:02 p.m. |
| NEDg | Description generation | batch_69d153aca5108190bcc9c830f48f595a |
completed | April 4, 2026, 6:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1577105988190a6e6aebc16e9421d |
completed | April 4, 2026, 6:24 p.m. |
Created at: March 9, 2026, 3:37 p.m.