Triple
T24490293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | chirigotas |
E617622
|
entity |
| Predicate | typicalLanguageVariant |
P5595
|
FINISHED |
| Object | Andalusian Spanish |
—
|
NE NERFINISHED |
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: Andalusian Spanish | Statement: [chirigotas, typicalLanguageVariant, Andalusian Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalLanguageVariant Context triple: [chirigotas, typicalLanguageVariant, Andalusian Spanish]
-
A.
linguisticVariant
Indicates that one linguistic form is an alternative version or expression of another within the same or closely related language context.
-
B.
officialLanguageVariant
Indicates that one language variety is an officially recognized form or version of another language within a specific jurisdiction or context.
-
C.
languageVariant
chosen
Indicates that one language is a variant, dialect, or localized form of another language.
-
D.
workLanguageVariant
Indicates that one language variant of a work is related to another version of the same work, typically differing by language or localization.
-
E.
regionalVariantOf
Indicates that one entity is a version or form of another that is specific to a particular geographic region or locale.
- 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_69e2d7f4e6bc8190aec540ae3b9ed7f2 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f2a9d912e88190bc39c05a9d7f407e |
completed | April 30, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69f2a6a4580481908fddc385f5262f95 |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:22 a.m.