Triple
T14446600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lewedorp |
E358223
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Borsele |
E73295
|
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: Borsele | Statement: [Lewedorp, partOf, Borsele]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Borsele Context triple: [Lewedorp, partOf, Borsele]
-
A.
Borsele
chosen
Borsele is a municipality in the Dutch province of Zeeland, known for its rural landscape, villages, and the nearby Borssele nuclear power plant.
-
B.
Borssum
Borssum is a district of the seaport city of Emden in Lower Saxony, Germany, known primarily as a residential area with local amenities.
-
C.
Boskoop
Boskoop is a Dutch town historically renowned as a major center of tree and nursery cultivation.
-
D.
Borgloon
Borgloon is a historic town in the Belgian province of Limburg that once served as the political and administrative center of the medieval County of Loon.
-
E.
Zoersel
Zoersel is a municipality in the Belgian province of Antwerp, known for its green residential character and wooded surroundings.
- 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_69d82794dfa081909b9134ad2e32244b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9160126c8190a2862a1a3dde1aff |
completed | April 14, 2026, 7:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5bdf451c8190baaa3f7500eaea16 |
completed | May 8, 2026, 3:43 a.m. |
Created at: April 10, 2026, 1:19 a.m.