Triple
T791889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grevelingen |
E16931
|
entity |
| Predicate | hasPort |
P35
|
FINISHED |
| Object | Brouwershaven |
E302174
|
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: Brouwershaven | Statement: [Grevelingen, hasPort, Brouwershaven]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brouwershaven Context triple: [Grevelingen, hasPort, Brouwershaven]
-
A.
Brouwershaven
chosen
Brouwershaven is a small historic town in the Dutch province of Zeeland, known for its maritime heritage and well-preserved old center.
-
B.
Hulst
Hulst is a historic fortified town and municipality in the Dutch province of Zeeland, near the border with Belgium.
-
C.
Hellevoetsluis
Hellevoetsluis is a historic Dutch port town known for its maritime heritage and coastal location in the western Netherlands.
-
D.
Alblasserdam
Alblasserdam is a town and municipality in the western Netherlands, situated along the Noord River and known for its proximity to the Kinderdijk windmills.
-
E.
Ouddorp
Ouddorp is a coastal village in the Netherlands known for its wide North Sea beaches and dunes, popular for tourism and water sports.
- 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_69a4936cb7448190914f5fe4b8d81607 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a798c7608190b9c79c52a1fe0859 |
completed | March 1, 2026, 8:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4fabfbf1c819082fe4ccfb65fc51b |
completed | March 14, 2026, 6:05 a.m. |
Created at: March 1, 2026, 7:38 p.m.