Triple
T22722724
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vercelli plain |
E561906
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | city of Vercelli |
—
|
NE NERFINISHED |
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: city of Vercelli | Statement: [Vercelli plain, locatedNear, city of Vercelli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: city of Vercelli Context triple: [Vercelli plain, locatedNear, city of Vercelli]
-
A.
Vercelli
chosen
Vercelli is a historic city in northern Italy’s Piedmont region, known for its medieval architecture and important role in rice cultivation.
-
B.
Verona
Verona is a historic city in northern Italy renowned for its well-preserved Roman architecture and its association with Shakespeare’s "Romeo and Juliet."
-
C.
Verona
Verona is a small borough in Allegheny County, Pennsylvania, situated along the Allegheny River just northeast of Pittsburgh.
-
D.
Verona
Verona is a small rural town in the Bega Valley region of New South Wales, Australia.
-
E.
Venaria
Venaria is a town in the Metropolitan City of Turin in northern Italy, known for the nearby UNESCO-listed Royal Palace of Venaria Reale.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e2454fc984819088213b58ee87a002 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f17926ae0c8190af8493cab6b15261 |
completed | April 29, 2026, 3:21 a.m. |
Created at: April 17, 2026, 3:20 p.m.