Triple
T4041096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Velsen |
E83948
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Velserbroek |
E318950
|
NE FINISHED |
How this triple was built (2 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: Velserbroek | Statement: [Velsen, contains, Velserbroek]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Velserbroek Context triple: [Velsen, contains, Velserbroek]
-
A.
Zuidbroek
Zuidbroek is a village in the province of Groningen in the northeastern Netherlands, known historically as a small canal-side settlement in a largely rural landscape.
-
B.
Lembeek
Lembeek is a village in the Belgian municipality of Halle, located along the Senne River in the province of Flemish Brabant.
-
C.
Bennebroek
chosen
Bennebroek is a small town in North Holland, Netherlands, known as one of the country’s smallest former municipalities before merging into Bloemendaal.
-
D.
Horebeke
Horebeke is a small rural municipality in the Flemish Ardennes region of East Flanders, Belgium.
-
E.
Borgerhout
Borgerhout is a densely populated, multicultural district of the Belgian city of Antwerp, known for its vibrant street life and diverse communities.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69b55649b75c819086b272f56ac73be4 |
completed | March 14, 2026, 12:36 p.m. |
Created at: March 9, 2026, 3:37 p.m.