Triple
T13611377
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vecht |
E325194
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Breukelen |
—
|
NE NERFINISHED |
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: Breukelen | Statement: [Vecht, flowsThrough, Breukelen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Breukelen Context triple: [Vecht, flowsThrough, Breukelen]
-
A.
Breukelen
chosen
Breukelen is a Dutch town in the province of Utrecht, known as the namesake of Brooklyn in New York City.
-
B.
Deurne
Deurne is a district of the Belgian city of Antwerp, known for its residential neighborhoods and green spaces such as Rivierenhof park.
-
C.
Deurne
Deurne is a municipality in the Dutch province of North Brabant, known for its rural character and historic peat extraction areas.
-
D.
Groesbeek
Groesbeek is a village in the Dutch province of Gelderland, known for its hilly landscape, World War II history, and wine production.
-
E.
Geleen
Geleen is a town in the Dutch province of Limburg known historically for its coal mining industry and later as part of the chemical and industrial hub around Sittard-Geleen.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb0aa9a1481908c6f92495aff86c6 |
completed | April 12, 2026, 2:48 p.m. |
Created at: April 9, 2026, 9:50 p.m.