Triple
T15319429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heeze-Leende |
E366248
|
entity |
| Predicate | borderedBy |
P224
|
FINISHED |
| Object | Someren |
E615463
|
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: Someren | Statement: [Heeze-Leende, borderedBy, Someren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Someren Context triple: [Heeze-Leende, borderedBy, Someren]
-
A.
Someren
chosen
Someren is a municipality and town in the province of North Brabant in the southern Netherlands.
-
B.
Noorden
Noorden is a village in the Dutch province of South Holland, known for its rural character and surrounding lakes and peatland nature reserves.
-
C.
Voskuijl
Voskuijl is a Dutch surname most notably associated with Bep Voskuijl, one of the helpers of Anne Frank and her family during their time in hiding.
-
D.
Landsmeer
Landsmeer is a small Dutch town and municipality in North Holland, situated just north of Amsterdam and known for its watery landscapes and nature reserves.
-
E.
Vandamm
Vandamm is a surname, often a variant spelling of "van Damm," associated with various individuals in arts, entertainment, and other fields.
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03dd356b881908f054b64eee6a371 |
completed | April 16, 2026, 1:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fef8a9085881909904152c32b0fed1 |
completed | May 9, 2026, 9:04 a.m. |
Created at: April 10, 2026, 3:16 a.m.