Triple
T15842620
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minardi (historical) |
E384134
|
entity |
| Predicate | basedIn |
P40
|
FINISHED |
| Object | Faenza, Italy |
E386577
|
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: Faenza, Italy | Statement: [Minardi (historical), basedIn, Faenza, Italy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Faenza, Italy Context triple: [Minardi (historical), basedIn, Faenza, Italy]
-
A.
Faenza
chosen
Faenza is a historic city in Italy’s Emilia-Romagna region, renowned for its traditional ceramics and artistic majolica production.
-
B.
Formia, Italy
Formia is a coastal town in the Lazio region of central Italy, known for its ancient Roman heritage and scenic location along the Gulf of Gaeta.
-
C.
Montecarotto, Italy
Montecarotto, Italy is a small hilltop town in the Marche region known for its medieval historic center, wine production, and traditional cultural festivals.
-
D.
Montella, Italy
Montella, Italy is a small town in the Campania region of southern Italy, known for its mountainous landscape and traditional chestnut production.
-
E.
Calenzano, Italy
Calenzano, Italy is a Tuscan municipality near Florence known for its medieval castle, historic hilltop village, and mix of industrial and residential areas.
- 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_69d86da34c888190976e06c4019d415a |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e142e88ff08190a1035269e8fdaa6a |
completed | April 16, 2026, 8:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa93ddce4819086174b2549f5e12b |
completed | May 9, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:50 a.m.