Triple
T17586122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La terra trema |
E428325
|
entity |
| Predicate | languageVariantUsed |
P123131
|
FINISHED |
| Object | Sicilian 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: Sicilian dialect | Statement: [La terra trema, languageVariantUsed, Sicilian dialect]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageVariantUsed Context triple: [La terra trema, languageVariantUsed, Sicilian dialect]
-
A.
languageVariant
Indicates that one language is a variant, dialect, or localized form of another language.
-
B.
linguisticVariant
Indicates that one linguistic form is an alternative version or expression of another within the same or closely related language context.
-
C.
workLanguageVariant
chosen
Indicates that one language variant of a work is related to another version of the same work, typically differing by language or localization.
-
D.
usesLocalLanguageVariant
Indicates that an entity employs a region-specific or localized form of a language rather than a standard or global variant.
-
E.
officialLanguageVariant
Indicates that one language variety is an officially recognized form or version of another language within a specific jurisdiction or context.
- 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_69d889e1030481909950e140c63255b9 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e463d22f908190ae0f1eeafbe54459 |
completed | April 19, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fff0348190b899a32da537eaca |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:50 a.m.