Triple
T10947129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prinses Margrietkanaal |
E258625
|
entity |
| Predicate | nearbyTown |
P3883
|
FINISHED |
| Object | Sneek |
E375572
|
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: Sneek | Statement: [Prinses Margrietkanaal, nearbyTown, Sneek]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sneek Context triple: [Prinses Margrietkanaal, nearbyTown, Sneek]
-
A.
Sneek
chosen
Sneek is a historic Dutch city known for its waterways, sailing culture, and the iconic Waterpoort gate.
-
B.
Delfzijl
Delfzijl is a port town in the northeast of the Netherlands, known for its maritime industry and location on the Ems estuary near the German border.
-
C.
Nieuwendam
Nieuwendam is a historic neighborhood in the northern part of Amsterdam, known for its former village character and waterfront location along the IJ.
-
D.
Buitendijk
Buitendijk is a Dutch surname borne by individuals such as academic leader Simone Buitendijk.
-
E.
Spaarndam
Spaarndam is a historic Dutch village in North Holland, known for its old sluices and dikes along the river Spaarne and its traditional waterfront charm.
- 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_69d6aa8769b4819082bfe5e61b9017f0 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770eaaea08190b06e508600d8a305 |
completed | April 9, 2026, 9:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff7559f0448190a992f0770ac8227a |
completed | May 9, 2026, 5:56 p.m. |
Created at: April 8, 2026, 9:23 p.m.