Triple
T22424907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brindisini |
E554342
|
entity |
| Predicate | usesGentilicInItalian |
P105483
|
FINISHED |
| Object | Brindisini |
—
|
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: Brindisini | Statement: [Brindisini, usesGentilicInItalian, Brindisini]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesGentilicInItalian Context triple: [Brindisini, usesGentilicInItalian, Brindisini]
-
A.
usesGentilicFor
chosen
Indicates that one entity refers to another using a gentilic (a demonym or term denoting origin, nationality, or regional affiliation).
-
B.
gentilicium
Indicates that an entity’s family or clan affiliation is expressed through a gentilic (family) name.
-
C.
hasGenderInItalian
Indicates that an entity is associated with a specific grammatical gender when expressed in the Italian language.
-
D.
nameInItalian
Indicates that one entity is the Italian-language name or label used to refer to another entity.
-
E.
gentilicLanguage
Indicates that a language is associated with or derived from a particular gentilic (demonym) for a people or place.
- 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_69e11e4f2d0c819091aa3558ea2ee630 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15a2c47bc81908b8265d83fa6fb65 |
completed | April 29, 2026, 1:09 a.m. |
| PD | Predicate disambiguation | batch_69e898a327948190beee5e168006a0a7 |
completed | April 22, 2026, 9:45 a.m. |
Created at: April 16, 2026, 8:47 p.m.