Triple
T13021727
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harderwijk |
E326186
|
entity |
| Predicate | hasDemonym |
P191
|
FINISHED |
| Object | Harderwijker |
E326186
|
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: Harderwijker | Statement: [Harderwijk, hasDemonym, Harderwijker]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harderwijker Context triple: [Harderwijk, hasDemonym, Harderwijker]
-
A.
Harderwijk
chosen
Harderwijk is a historic Dutch city known for its former Hanseatic trading role and scenic location on the shores of the Veluwemeer.
-
B.
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.
-
C.
Waalwijk
Waalwijk is a town and municipality in the southern Netherlands known historically for its leather and shoe industry.
-
D.
Winterswijk
Winterswijk is a town in the eastern Netherlands known for its rural landscape, textile-industry history, and location near the German border.
-
E.
Veldhoven
Veldhoven is a town and municipality in the southern Netherlands, located near Eindhoven in the province of North Brabant.
- 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_69d8076cc45c81908123123f43e69266 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97ed05e9c8190a4f208662bca0602 |
completed | April 10, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6c119e19c81908ae2b1caff6f2f32 |
completed | May 3, 2026, 3:29 a.m. |
Created at: April 9, 2026, 8:52 p.m.