Triple
T19390957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canosini |
E485064
|
entity |
| Predicate | usesGentilicPlural |
P107812
|
FINISHED |
| Object | Canosini (masculine plural) |
—
|
LITERAL 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: Canosini (masculine plural) | Statement: [Canosini, usesGentilicPlural, Canosini (masculine plural)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesGentilicPlural Context triple: [Canosini, usesGentilicPlural, Canosini (masculine plural)]
-
A.
usesGentilicFor
Indicates that one entity refers to another using a gentilic (a demonym or term denoting origin, nationality, or regional affiliation).
-
B.
genderedPluralForm
chosen
Indicates that the plural form of a term is specifically marked or inflected to reflect a particular gender.
-
C.
gentilicLanguage
Indicates that a language is associated with or derived from a particular gentilic (demonym) for a people or place.
-
D.
usesDemonymForm
Indicates that one entity refers to another using a demonym form, i.e., a name derived from the inhabitants or nationality associated with that entity.
-
E.
usesPersonalNamesFrom
Indicates that one entity employs or adopts the system or set of personal names originating from another entity.
- F. None of above.
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_69d8e8d460d88190abf0591c5c9d2b0c |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e61b44b70c81908e2f0deeabe4360f |
completed | April 20, 2026, 12:25 p.m. |
| PD | Predicate disambiguation | batch_69e4fd602f008190aa9bc76ae17e4ce1 |
completed | April 19, 2026, 4:05 p.m. |
Created at: April 10, 2026, 1:36 p.m.