Triple
T13544083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stichtse Vecht |
E323466
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Maarssen |
—
|
NE NERFINISHED |
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: Maarssen | Statement: [Stichtse Vecht, hasSettlement, Maarssen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maarssen Context triple: [Stichtse Vecht, hasSettlement, Maarssen]
-
A.
Maarssen
chosen
Maarssen is a town in the Dutch province of Utrecht, situated along the river Vecht and functioning largely as a residential and commuter community near the city of Utrecht.
-
B.
Geldermalsen
Geldermalsen is a town in the Dutch province of Gelderland known as a regional transport hub and former municipality surrounded by fruit-growing countryside.
-
C.
Hansweert
Hansweert is a small village in the Dutch province of Zeeland, known historically as a canal and shipping hub along the Western Scheldt.
-
D.
Nunspeet
Nunspeet is a Dutch town and municipality on the Veluwe known for its forests, heathlands, and role as a popular nature and holiday destination.
-
E.
Maasdijk
Maasdijk is a village in the Dutch province of South Holland, known for its greenhouse horticulture and proximity to the North Sea coast.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8076776248190bdf0d4fa1f85a5fc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafda36248190acabde65a88c5471 |
completed | April 12, 2026, 2:44 p.m. |
Created at: April 9, 2026, 9:45 p.m.