Triple
T1321582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Piedmont |
E28229
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object | Vercelli |
E243615
|
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: Vercelli | Statement: [Piedmont, containsCity, Vercelli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vercelli Context triple: [Piedmont, containsCity, 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.
Pavia
Pavia is a historic city in northern Italy, known for its ancient university, medieval architecture, and significant role in Lombardy’s cultural and academic life.
-
C.
Biella
Biella is a city in the Piedmont region of northern Italy, known for its textile industry and Alpine foothill setting.
-
D.
Alessandria
Alessandria is a city in the Piedmont region of northwestern Italy, known as an important industrial and transportation hub.
-
E.
Cuneo
Cuneo is a city in the Piedmont region of northwestern Italy, known for its Alpine setting, agricultural traditions, and use of the Piedmontese language.
- 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_69a498540a2481909e807a762280d3ba |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c19932888190a3d45871e84f112e |
completed | March 1, 2026, 10:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af1f66dfd48190831981703142066a |
completed | March 9, 2026, 7:28 p.m. |
Created at: March 1, 2026, 7:55 p.m.