Triple
T4971977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | special statute region |
E111673
|
entity |
| Predicate | hasLegalNameInItalian |
P17612
|
FINISHED |
| Object | regione a statuto speciale |
—
|
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: regione a statuto speciale | Statement: [special statute region, hasLegalNameInItalian, regione a statuto speciale]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLegalNameInItalian Context triple: [special statute region, hasLegalNameInItalian, regione a statuto speciale]
-
A.
nameInItalian
chosen
Indicates that one entity is the Italian-language name or label used to refer to another entity.
-
B.
hasOfficialNameInLatin
Indicates that an entity has an official or formally recognized name expressed in the Latin language.
-
C.
hasInternationalName
Indicates that an entity is associated with a name used or recognized in an international or cross-linguistic context.
-
D.
hasLatinName
Indicates that an entity is associated with a specific Latin (scientific) name.
-
E.
hasNameInLocalLanguage
Indicates that an entity is associated with a name expressed in the local or native language of a given context or region.
- 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_69bd441a0eb481908050fa4273b19eae |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd730a7590819088ab8d49c5c88c2f |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd7146e6e881908a55ab2756b631f6 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:33 p.m.