Triple
T5096567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hollands Diep |
E114879
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Willemstad |
E445344
|
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: Willemstad | Statement: [Hollands Diep, near, Willemstad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Willemstad Context triple: [Hollands Diep, near, Willemstad]
-
A.
Willemstad
Willemstad is the colorful, Dutch colonial-style port city that serves as the capital and cultural center of the Caribbean island of Curaçao.
-
B.
Kralendijk
Kralendijk is the main town and administrative center of the island of Bonaire in the Caribbean.
-
C.
Oranjestad
Oranjestad is the largest city and main commercial and tourism hub of Aruba, located on the island’s western coast.
-
D.
Oranjestad
Oranjestad is the main town and administrative center of the Caribbean island of Sint Eustatius, known for its historic colonial architecture and coastal setting.
-
E.
Zaandam
chosen
Zaandam is a city in the North Holland province of the Netherlands, known for its historic windmills, traditional wooden houses, and proximity to Amsterdam.
- 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_69bd443fc49c819089629c00e311310c |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd75652a8081908386718f1fdb1de3 |
completed | March 20, 2026, 4:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beba80aee081908498cbe9d4f2eaa7 |
completed | March 21, 2026, 3:34 p.m. |
Created at: March 20, 2026, 1:40 p.m.