Triple
T21193792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benedetto Alfieri |
E522274
|
entity |
| Predicate | workLocation |
P7
|
FINISHED |
| Object | Alessandria |
—
|
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: Alessandria | Statement: [Benedetto Alfieri, workLocation, Alessandria]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alessandria Context triple: [Benedetto Alfieri, workLocation, Alessandria]
-
A.
Alessandria
chosen
Alessandria is a city in the Piedmont region of northwestern Italy, known as an important industrial and transportation hub.
-
B.
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.
-
C.
Biella
Biella is a city in the Piedmont region of northern Italy, known for its textile industry and Alpine foothill setting.
-
D.
Orbassano
Orbassano is a town and comune in the Metropolitan City of Turin in the Piedmont region of northwestern Italy.
-
E.
Tortona
Tortona is a historic town in the Piedmont region of northern Italy, known for its medieval architecture and strategic location between Milan and Genoa.
- 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_69e0b51061388190aa03f19700d3ef04 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e73339aaa081909d9009c58c386422 |
completed | April 21, 2026, 8:20 a.m. |
Created at: April 16, 2026, 3:08 p.m.