Triple
T16047908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rijnmond region |
E389271
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Ridderkerk |
E180392
|
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: Ridderkerk | Statement: [Rijnmond region, hasMunicipality, Ridderkerk]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ridderkerk Context triple: [Rijnmond region, hasMunicipality, Ridderkerk]
-
A.
Ridderkerk
chosen
Ridderkerk is a town and municipality in the western Netherlands, situated near Rotterdam in the province of South Holland.
-
B.
Grijpskerke
Grijpskerke is a village in the Dutch province of Zeeland, located on the former island of Walcheren.
-
C.
Kortenaken
Kortenaken is a rural municipality in the Flemish Brabant province of Belgium, known for its agricultural landscape and small village communities.
-
D.
Valkenswaard
Valkenswaard is a town in the southern Netherlands known for its strong equestrian culture and international show jumping events.
-
E.
Rijkevoort
Rijkevoort is a village in the Dutch province of North Brabant, known for its rural character and location near the German border.
- 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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e18360464881909fd4d3bcb4ffb7f5 |
completed | April 17, 2026, 12:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f39008c819095ad8512eb119ee8 |
completed | May 10, 2026, 9:26 a.m. |
Created at: April 10, 2026, 4:56 a.m.