Triple
T5096553
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hollands Diep |
E114879
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Biesbosch |
E17509
|
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: Biesbosch | Statement: [Hollands Diep, connectsTo, Biesbosch]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Biesbosch Context triple: [Hollands Diep, connectsTo, Biesbosch]
-
A.
Biesbosch
chosen
Biesbosch is a large freshwater tidal wetland and national park in the Netherlands, known for its intricate network of rivers, creeks, and rich birdlife.
-
B.
Brielse Meer
Brielse Meer is a former estuarine inlet in South Holland, Netherlands, now a dammed-off lake popular for recreation and water sports.
-
C.
Sappemeer
Sappemeer is a town in the province of Groningen in the northeastern Netherlands, historically known for its peat colonies and waterways.
-
D.
Oldambtmeer
Oldambtmeer is an artificial lake in the municipality of Oldambt in the province of Groningen, Netherlands, created as part of a large-scale landscape and recreational development project.
-
E.
Vechta
Vechta is a town in Lower Saxony, Germany, known for its historical significance, university, and annual Stoppelmarkt fair.
- 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_69bd443fc49c819089629c00e311310c |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75652a8081908386718f1fdb1de3 |
completed | March 20, 2026, 4:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bee067be548190b280674ebf125ca3 |
completed | March 21, 2026, 6:16 p.m. |
Created at: March 20, 2026, 1:40 p.m.