Triple
T7342237
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Katwijk |
E169281
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Wassenaar |
E174773
|
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: Wassenaar | Statement: [Katwijk, borderedBy, Wassenaar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wassenaar Context triple: [Katwijk, borderedBy, Wassenaar]
-
A.
Wassenaar
chosen
Wassenaar is an affluent coastal town in the western Netherlands known for its wooded estates, beaches, and role as a residential area for diplomats and expatriates.
-
B.
Yerseke
Yerseke is a Dutch village in the province of Zeeland, best known for its mussel and oyster farming along the Eastern Scheldt.
-
C.
Esens
Esens is a small historic town in Lower Saxony, Germany, known for its coastal North Sea location and traditional East Frisian character.
-
D.
Wateringen
Wateringen is a town in the western Netherlands that forms part of the municipality of Westland in the province of South Holland.
-
E.
Wassen
Wassen is a small Swiss village in the canton of Uri, known for its picturesque church and location along the Gotthard railway and road routes in the central Alps.
- 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_69c68a57710481909f0c1f3c6ebdb6f2 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f0db2db8819088c4bed5d65571f6 |
completed | March 27, 2026, 9:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c9bcbe7f488190aee034a51e8a281b |
completed | March 29, 2026, 11:58 p.m. |
Created at: March 27, 2026, 3:04 p.m.