Triple
T13704229
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eemnes |
E328597
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Wijdemeren |
—
|
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: Wijdemeren | Statement: [Eemnes, borderedBy, Wijdemeren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wijdemeren Context triple: [Eemnes, borderedBy, Wijdemeren]
-
A.
Wijdemeren
chosen
Wijdemeren is a municipality in the Dutch province of North Holland, known for its lakes, waterways, and scenic rural landscapes.
-
B.
Veldhoven
Veldhoven is a town and municipality in the southern Netherlands, located near Eindhoven in the province of North Brabant.
-
C.
Waalwijk
Waalwijk is a town and municipality in the southern Netherlands known historically for its leather and shoe industry.
-
D.
Zwijndrecht
Zwijndrecht is a Dutch town and municipality located in the western Netherlands, known for its position along the rivers near the city of Dordrecht.
-
E.
Steenwijk
Steenwijk is a historic town in the Dutch province of Overijssel, known for its medieval center and role as a regional hub in the north of the province.
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dcad162158819089280ee1e6b5c2cf |
completed | April 13, 2026, 8:45 a.m. |
Created at: April 9, 2026, 9:54 p.m.