Triple
T21313471
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arnemuiden railway station |
E525403
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Arnemuiden |
—
|
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: Arnemuiden | Statement: [Arnemuiden railway station, locatedIn, Arnemuiden]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arnemuiden Context triple: [Arnemuiden railway station, locatedIn, Arnemuiden]
-
A.
Arnemuiden
chosen
Arnemuiden is a small historic town in the Dutch province of Zeeland, known for its maritime heritage and traditional fishing culture.
-
B.
Sneekermeer
Sneekermeer is a popular lake in the Dutch province of Friesland, known for boating, sailing, and water sports near the city of Sneek.
-
C.
Heessen
Heessen is a district of the German city of Hamm, located in the state of North Rhine-Westphalia.
-
D.
Monnickendam
Monnickendam is a historic fishing town in North Holland, Netherlands, known for its well-preserved old harbor and traditional Dutch architecture.
-
E.
Eemsmond
Eemsmond was a former municipality in the province of Groningen in the Netherlands, located in the far north along the Wadden Sea coast.
- 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_69e0b518b8948190ad69cf9a8784d397 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e75dcc6350819093763632b7e6e4ac |
completed | April 21, 2026, 11:21 a.m. |
Created at: April 16, 2026, 4:27 p.m.