Triple
T4747716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German-speaking Italy |
E105401
|
entity |
| Predicate | bilingualSignage |
P4196
|
FINISHED |
| Object | German and 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: German and Italian | Statement: [German-speaking Italy, bilingualSignage, German and Italian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bilingualSignage Context triple: [German-speaking Italy, bilingualSignage, German and Italian]
-
A.
officialLanguageOfSignage
Indicates that a particular language is the one officially used on public signs and signage within a given place or context.
-
B.
languageOfSignage
chosen
Indicates the language used on signs or written displays associated with an entity.
-
C.
tertiaryLanguageOfSignage
Indicates that a language is used as the third-most prominent language on signage in a given context or location.
-
D.
isBilingual
Indicates that an entity is able to communicate fluently in two distinct languages.
-
E.
bilingualName
Indicates that an entity has a name expressed in two different languages, linking the entity to its bilingual designation.
- 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_69bd43f07fa48190954317d01600994a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd64c567288190a420e6825ee72822 |
completed | March 20, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69bd6223defc8190823665a6592c1154 |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:20 p.m.