Triple
T15704613
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Keutenberg |
E380674
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Heuvelland |
E1172150
|
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: Heuvelland | Statement: [Keutenberg, region, Heuvelland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heuvelland Context triple: [Keutenberg, region, Heuvelland]
-
A.
Heuvelland
chosen
Heuvelland is a hilly region in the southern Netherlands known for its scenic landscapes, cycling routes, and picturesque villages.
-
B.
Heinenoord
Heinenoord is a village in the Dutch province of South Holland, known for its rural character and the nearby Heinenoord Tunnel under the Oude Maas river.
-
C.
Veenendaal
Veenendaal is a Dutch town and municipality in the central Netherlands, known for its location between Utrecht and the Veluwe and its mix of residential, commercial, and light industrial areas.
-
D.
Holleken
Holleken is a local railway station serving the suburban area near Brussels, Belgium.
-
E.
Molenstad
Molenstad is the Dutch nickname for the town of Winschoten, referring to its notable association with windmills.
- 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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f6fc3608190a85b25755f5345db |
completed | April 16, 2026, 2:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff82f05d648190a0c73b60dc027287 |
completed | May 9, 2026, 6:54 p.m. |
Created at: April 10, 2026, 4:45 a.m.