Triple
T3014156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bloemendaal |
E82295
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Zandvoort |
E126133
|
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: Zandvoort | Statement: [Bloemendaal, locatedNear, Zandvoort]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zandvoort Context triple: [Bloemendaal, locatedNear, Zandvoort]
-
A.
Zandvoort
chosen
Zandvoort is a Dutch coastal town on the North Sea known for its sandy beaches and the nearby Circuit Zandvoort motor racing track.
-
B.
Assen
Assen is a city in the northeastern Netherlands best known as the capital of the province of Drenthe and for hosting the annual TT Circuit motorcycle races.
-
C.
Scheveningen
Scheveningen is a popular seaside resort district of The Hague in the Netherlands, known for its long sandy beach, pier, and promenade along the North Sea coast.
-
D.
Papendrecht
Papendrecht is a Dutch town situated on the river Merwede in the province of South Holland, known for its residential character and proximity to the city of Dordrecht.
-
E.
Zoetermeer
Zoetermeer is a modern, rapidly grown satellite city of The Hague in the western Netherlands, known for its residential neighborhoods and light-rail connections.
- 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_69ad8b1eb53481908c39bbcd1ec104b2 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a69e8148190a97507740c9d26a8 |
completed | March 8, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1dea9a7c4819087fb6853d839fb1e |
completed | March 11, 2026, 9:29 p.m. |
Created at: March 8, 2026, 3 p.m.