Triple
T8222393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gunfleet Sands |
E192094
|
entity |
| Predicate | gridConnectionPoint |
P25653
|
FINISHED |
| Object | Holland-on-Sea |
E290186
|
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: Holland-on-Sea | Statement: [Gunfleet Sands, gridConnectionPoint, Holland-on-Sea]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Holland-on-Sea Context triple: [Gunfleet Sands, gridConnectionPoint, Holland-on-Sea]
-
A.
Holland-on-Sea
chosen
Holland-on-Sea is a coastal town in Essex, England, known for its quiet residential character and sandy beaches along the North Sea.
-
B.
Veendam
Veendam is a town and municipality in the province of Groningen in the northeastern Netherlands, historically known for peat extraction and later for its industrial development.
-
C.
Londerzeel
Londerzeel is a municipality in the Flemish Brabant province of Belgium, known for its residential character and proximity to both Brussels and Antwerp.
-
D.
De Koog
De Koog is a coastal village and popular seaside resort on the Dutch Wadden Island of Texel, known for its beaches, dunes, and tourism.
-
E.
Eemshaven
Eemshaven is a major seaport and energy hub in the north of the Netherlands, known for its power plants, data centers, and offshore wind connections.
- 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_69ca82c9a8ac81908b011c38698456e4 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb77cae2948190ae4507b75b5d5784 |
completed | March 31, 2026, 7:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccee09ac548190a9988ff77d43e77e |
completed | April 1, 2026, 10:06 a.m. |
Created at: March 30, 2026, 5:45 p.m.