Triple
T3046005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nijmegen railway station |
E83447
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Arnhem |
E12070
|
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: Arnhem | Statement: [Nijmegen railway station, connectsTo, Arnhem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arnhem Context triple: [Nijmegen railway station, connectsTo, Arnhem]
-
A.
Arnhem
chosen
Arnhem is a city in the eastern Netherlands best known as the site of a major World War II battle during Operation Market Garden.
-
B.
Leeuwarden
Leeuwarden is a historic city in the northern Netherlands, known as the capital of the province of Friesland and for its rich cultural and architectural heritage.
-
C.
Papendrecht
Papendrecht is a Dutch town situated on the river Merwede in the province of South Holland, known for its residential character and proximity to the city of Dordrecht.
-
D.
Gorinchem
Gorinchem is a historic fortified city in the Netherlands known for its well-preserved city walls and picturesque old town.
-
E.
Apeldoorn
Apeldoorn is a city in the province of Gelderland in the Netherlands, known for the royal palace Het Loo and its historical ties to the Dutch monarchy.
- 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_69ad8b24924c8190a9bb6f61d519e4ae |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9bab541c8190a17aca26b3dcfae7 |
completed | March 8, 2026, 3:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1eef43da8819094cd438c93c64c86 |
completed | March 11, 2026, 10:38 p.m. |
Created at: March 8, 2026, 3:01 p.m.