Triple
T6733758
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neapolitan Bourbons |
E153701
|
entity |
| Predicate | languageUsedAtCourt |
P6495
|
FINISHED |
| Object | Italian |
—
|
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: Italian | Statement: [Neapolitan Bourbons, languageUsedAtCourt, Italian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageUsedAtCourt Context triple: [Neapolitan Bourbons, languageUsedAtCourt, Italian]
-
A.
courtLanguage
chosen
Indicates the language officially used in legal proceedings or by a court.
-
B.
languageOfJurisdiction
Indicates the language officially used for legal and administrative purposes within a given jurisdiction.
-
C.
languageUsedAs
Indicates that one language is employed in a specific role, function, or context relative to another entity or situation.
-
D.
languageOfCommunications
Indicates that a specified language is used as the medium for communications associated with an entity or interaction.
-
E.
languageOfInterpretation
Indicates the language in which something (such as text, speech, or content) is interpreted or understood.
- 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_69c6880bdd68819097de8b6099992682 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d354177481908ab3cf5437c095e2 |
completed | March 27, 2026, 6:58 p.m. |
| PD | Predicate disambiguation | batch_69c6d08e8a2c8190ae4e8d8c039be7ce |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:09 p.m.