Triple
T17174243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rheden |
E416816
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Doesburg |
E172118
|
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: Doesburg | Statement: [Rheden, borderedBy, Doesburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Doesburg Context triple: [Rheden, borderedBy, Doesburg]
-
A.
Doesburg
chosen
Doesburg is a historic city in the Dutch province of Gelderland, known for its well-preserved medieval center and location at the confluence of the IJssel and Oude IJssel rivers.
-
B.
Vredenburg
Vredenburg is a former name of the Muziekcentrum Vredenburg, a prominent concert and music venue in Utrecht, Netherlands.
-
C.
Vredenburg
Vredenburg is a town on South Africa’s West Coast that serves as a regional commercial and service hub near Saldanha Bay.
-
D.
Batenburg
Batenburg is a small historic town in the Dutch province of Gelderland, known for its medieval castle ruins and picturesque setting along the river Maas.
-
E.
Dieburg
Dieburg is a small historic town in the German state of Hesse, known for its medieval old town and regional administrative role.
- 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_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3fc0c329081909f118bd4b7be8653 |
completed | April 18, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0148435f6081909bfc6cc1ef59d971 |
completed | May 11, 2026, 3:08 a.m. |
Created at: April 10, 2026, 5:37 a.m.