Triple
T1090936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Holland |
E24160
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Alkmaar |
E445674
|
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: Alkmaar | Statement: [North Holland, contains, Alkmaar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alkmaar Context triple: [North Holland, contains, Alkmaar]
-
A.
Alkmaar
chosen
Alkmaar is a historic city in the Netherlands, renowned for its traditional cheese market and well-preserved medieval center.
-
B.
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.
-
C.
Gorinchem
Gorinchem is a historic fortified city in the Netherlands known for its well-preserved city walls and picturesque old town.
-
D.
Hellevoetsluis
Hellevoetsluis is a historic Dutch port town known for its maritime heritage and coastal location in the western Netherlands.
-
E.
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.
- 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_69a49404428c819092dcc9632f5f7b8b |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b980c8448190b08c3a9a7e7f4e85 |
completed | March 1, 2026, 10:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be5c5e461c8190b4c7f728e2d8632c |
completed | March 21, 2026, 8:52 a.m. |
Created at: March 1, 2026, 7:42 p.m.