Triple
T7129664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monferrato |
E166153
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Canelli |
E467472
|
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: Canelli | Statement: [Monferrato, contains, Canelli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Canelli Context triple: [Monferrato, contains, Canelli]
-
A.
Canelli
chosen
Canelli is a town in Italy’s Piedmont region renowned for its historic wine production and UNESCO-listed underground wine cellars.
-
B.
Biqueli
Biqueli is a small coastal settlement on Atauro Island in East Timor, known for its fishing community and proximity to coral reefs.
-
C.
Pecci
Pecci is the Italian noble family from which Pope Leo XIII, born Vincenzo Gioacchino Pecci, originated.
-
D.
Vignale
Vignale was an Italian coachbuilder and design house renowned for crafting elegant custom bodies for marques such as Lancia, Ferrari, and Maserati in the mid-20th century.
-
E.
Vignale
Vignale is a locality historically associated with the Italian coastal principality centered on Piombino in Tuscany.
- 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_69c6888350588190870cd552b427a1cd |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e66c87848190b0ffd08e3c3f4877 |
completed | March 27, 2026, 8:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7a33bf244819096db1351ebf62413 |
completed | March 28, 2026, 9:45 a.m. |
Created at: March 27, 2026, 2:44 p.m.