Triple
T14185374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gouda railway station |
E351560
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | city of Gouda |
E1086239
|
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: city of Gouda | Statement: [Gouda railway station, serves, city of Gouda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: city of Gouda Context triple: [Gouda railway station, serves, city of Gouda]
-
A.
Municipality of Gouda
chosen
The Municipality of Gouda is the local government authority responsible for administering the historic Dutch city of Gouda, renowned for its cheese, canals, and medieval architecture.
-
B.
Gouda city centre
Gouda city centre is the historic heart of the Dutch city of Gouda, known for its medieval architecture, cheese heritage, and atmospheric public squares.
-
C.
City of Holland
The City of Holland is a Michigan community known for its Dutch heritage, tulip festivals, and attractions like historic windmills and themed gardens.
-
D.
Leerdam
Leerdam is a Dutch city renowned for its glassmaking tradition, located in the province of South Holland.
-
E.
Deventer
Deventer is a historic Dutch city known for its medieval architecture, Hanseatic trading past, and annual book market.
- 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_69d8278834a08190b0f1784e58d7b99c |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61cd5778819092a03597bcdcc182 |
completed | April 14, 2026, 3:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd280656a881909c565b99e85ae9bd |
completed | May 8, 2026, 12:02 a.m. |
Created at: April 10, 2026, 1:03 a.m.