Triple
T10619569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wanze |
E295672
|
entity |
| Predicate | hasMunicipalSection |
P10450
|
FINISHED |
| Object | Wanze (section) |
E295672
|
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: Wanze (section) | Statement: [Wanze, hasMunicipalSection, Wanze (section)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wanze (section) Context triple: [Wanze, hasMunicipalSection, Wanze (section)]
-
A.
Wanze
chosen
Wanze is a municipality in eastern Belgium situated along the Meuse River in the Walloon Region.
-
B.
Waner
Waner is a surname most notably associated with Baseball Hall of Famer Paul Waner, a star outfielder for the Pittsburgh Pirates in the early 20th century.
-
C.
Wanetsi
Wanetsi is a distinct and archaic variety of Pashto spoken by a small community in parts of Afghanistan and Pakistan.
-
D.
Wenteche
Wenteche are an indigenous Mapuche subgroup traditionally inhabiting inland valleys and foothill regions of south-central Chile.
-
E.
Wanroij
Wanroij is a village in the Dutch province of North Brabant, known for its rural character and location within the municipality of Land van Cuijk.
- 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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d6df6fc47c8190b77b61a7fd223d65 |
completed | April 8, 2026, 11:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d96b86a5bc8190863034cc91fdbbb9 |
completed | April 10, 2026, 9:28 p.m. |
Created at: April 8, 2026, 8:21 p.m.