Triple
T2990206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aalsmeer |
E80730
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Nieuwkoop |
E81382
|
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: Nieuwkoop | Statement: [Aalsmeer, borderedBy, Nieuwkoop]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nieuwkoop Context triple: [Aalsmeer, borderedBy, Nieuwkoop]
-
A.
Nieuwkoop
chosen
Nieuwkoop is a rural municipality and town in South Holland, Netherlands, known for its lakes, peatlands, and nature reserves.
-
B.
Maassluis
Maassluis is a historic port town in the province of South Holland in the Netherlands, situated along the Nieuwe Waterweg west of Rotterdam.
-
C.
Schoonhoven
Schoonhoven is a historic Dutch town in South Holland, renowned for its silver craftsmanship and picturesque riverside setting.
-
D.
Coevorden
Coevorden is a historic city and municipality in the northeastern Netherlands, known for its medieval fortress layout and strategic location near the German border.
-
E.
Gorinchem
Gorinchem is a historic fortified city in the Netherlands known for its well-preserved city walls and picturesque old town.
- 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_69ad8b16c3488190b47b6aa7a59a335b |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99de55208190bc56ecbe08638e5a |
completed | March 8, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c124d359ec819086420b7e00b8d630 |
completed | March 23, 2026, 11:32 a.m. |
Created at: March 8, 2026, 2:59 p.m.