Triple
T12217474
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Weststellingwerf |
E291122
|
entity |
| Predicate | seatOfGovernment |
P761
|
FINISHED |
| Object | Wolvega |
E287538
|
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: Wolvega | Statement: [Weststellingwerf, seatOfGovernment, Wolvega]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wolvega Context triple: [Weststellingwerf, seatOfGovernment, Wolvega]
-
A.
Wolvega
chosen
Wolvega is a town in the Dutch province of Friesland, known as the administrative center of the municipality of Weststellingwerf.
-
B.
Vegueta
Vegueta is the historic old quarter of Las Palmas de Gran Canaria, known for its colonial architecture, cobbled streets, and cultural landmarks.
-
C.
Dumbría
Dumbría is a small municipality in the province of A Coruña in Galicia, northwestern Spain, known for its rural landscapes and proximity to the rugged Atlantic coastline.
-
D.
Moura
Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
-
E.
Moura
Moura is a small coal-mining town in Central Queensland, Australia, known for its agricultural activities and history of mining disasters.
- 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_69d6ab65923081909acfc61b7a612233 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91c9419d48190b0037fe8edc681c4 |
completed | April 10, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f62a8c69308190bffae7b38cc5620b |
completed | May 2, 2026, 4:47 p.m. |
Created at: April 8, 2026, 9:51 p.m.