Triple
T1876354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaag en Braassem |
E39152
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Teylingen |
E81864
|
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: Teylingen | Statement: [Kaag en Braassem, borderedBy, Teylingen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Teylingen Context triple: [Kaag en Braassem, borderedBy, Teylingen]
-
A.
Teylingen
chosen
Teylingen is a municipality in the Dutch province of South Holland, known for its historic estates and proximity to the bulb-growing region.
-
B.
Uithoorn
Uithoorn is a town and municipality in the province of North Holland in the Netherlands, situated along the Amstel River.
-
C.
Biezelinge
Biezelinge is a small village in the Dutch province of Zeeland, known as the birthplace of former Prime Minister Jan Peter Balkenende.
-
D.
Holendrecht
Holendrecht is a metro station in Amsterdam serving the southeastern part of the city, including the nearby academic hospital and university campus.
-
E.
Oldenzaal
Oldenzaal is a historic city in the eastern Netherlands known for its medieval center and location near the German border in the province of Overijssel.
- 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_69a8862f7074819096afe7fe65e179e9 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb0d902ac8190a2d9bb6f683986e4 |
completed | March 7, 2026, 5 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af9040c20c8190aaae6f22fc893032 |
completed | March 10, 2026, 3:30 a.m. |
Created at: March 4, 2026, 7:34 p.m.