Triple
T7983197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mario Balotelli |
E185622
|
entity |
| Predicate | youthClub |
P1088
|
FINISHED |
| Object | Lumezzane |
E714906
|
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: Lumezzane | Statement: [Mario Balotelli, youthClub, Lumezzane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lumezzane Context triple: [Mario Balotelli, youthClub, Lumezzane]
-
A.
Lumezzane
chosen
Lumezzane is an Italian football club based in the town of Lumezzane in Lombardy, known for developing players such as Mario Balotelli.
-
B.
Lodigiano
Lodigiano is a regional variety of the Lombard language traditionally spoken in and around the city of Lodi in northern Italy.
-
C.
Legnago
Legnago is a town in the Veneto region of northern Italy, situated along the Adige River and known historically as a fortified center.
-
D.
Busto Arsizio
Busto Arsizio is an industrial city in the Lombardy region of northern Italy, known for its textile and manufacturing heritage and its location within the greater Milan metropolitan area.
-
E.
Lecco
Lecco is an Italian town in the Lombardy region, known for its scenic location at the southeastern tip of Lake Como and its surrounding Alpine foothills.
- 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_69ca829a2cfc819083d591d58ec04075 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c2a1aa881909c3cea280dff38f5 |
completed | March 31, 2026, 3:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ccec9e21d881908963dcc38bcc2df0 |
completed | April 1, 2026, 9:59 a.m. |
Created at: March 30, 2026, 5:15 p.m.