Triple
T19390934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canosini |
E485064
|
entity |
| Predicate | usesLocalDialect |
P73137
|
FINISHED |
| Object | Apulian dialect |
—
|
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: Apulian dialect | Statement: [Canosini, usesLocalDialect, Apulian dialect]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesLocalDialect Context triple: [Canosini, usesLocalDialect, Apulian dialect]
-
A.
usesLocalLanguageVariant
chosen
Indicates that an entity employs a region-specific or localized form of a language rather than a standard or global variant.
-
B.
usesDialect
Indicates that one entity communicates or expresses itself using the specific dialect associated with another entity.
-
C.
regulatesDialect
Indicates a relationship in which one entity controls, shapes, or constrains the form, usage, or rules of a particular dialect.
-
D.
focusesOnDialect
Indicates that the subject’s attention, work, or activity is specifically directed toward a particular dialect or set of dialects.
-
E.
consideredDialectOf
Indicates that one language variety is regarded as a dialect of another language or linguistic standard.
- 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.