Triple
T20376174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cannara |
E497697
|
entity |
| Predicate | hasDemonym |
P191
|
FINISHED |
| Object | Cannaresi |
—
|
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: Cannaresi | Statement: [Cannara, hasDemonym, Cannaresi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cannaresi Context triple: [Cannara, hasDemonym, Cannaresi]
-
A.
Cannara
chosen
Cannara is a small Italian town in the Umbria region, known for its agricultural traditions and annual onion festival.
-
B.
Cagni
Cagni is an Italian surname most notably associated with Luigi Cagni, a former professional footballer and football manager.
-
C.
Cesariny
Cesariny is the surname of Mário Cesariny de Vasconcelos Tavares, a prominent Portuguese surrealist poet and painter.
-
D.
Casarosa
Casarosa is an Italian surname most notably associated with Enrico Casarosa, the animator and director known for his work at Pixar.
-
E.
Mirandolesi
Mirandolesi are the inhabitants or natives of Mirandola, a town in the Emilia-Romagna region of northern Italy.
- 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_69e0b4a5b7908190a972e4e7e698ae94 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e678ad74348190ac57d38eaa56beb3 |
completed | April 20, 2026, 7:04 p.m. |
Created at: April 16, 2026, 11:27 a.m.