Triple
T25038671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bizkaia |
E627048
|
entity |
| Predicate | hasTraditionalLanguageVariant |
P28812
|
FINISHED |
| Object | Biscayan Basque 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: Biscayan Basque dialect | Statement: [Bizkaia, hasTraditionalLanguageVariant, Biscayan Basque dialect]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTraditionalLanguageVariant Context triple: [Bizkaia, hasTraditionalLanguageVariant, Biscayan Basque dialect]
-
A.
hasTraditionalLanguageRegion
Indicates the geographic region traditionally associated with the use or origin of a particular language.
-
B.
hasTraditionalDialect
chosen
Indicates that an entity possesses or is associated with a traditional form or variety of a language or dialect.
-
C.
hasPrimaryTraditionalLanguage
Indicates that one entity is the main or principal traditional language associated with another entity.
-
D.
languageVariant
Indicates that one language is a variant, dialect, or localized form of another language.
-
E.
hasTraditionalTranslation
Indicates that one entity serves as the established or customary translation of another entity in a traditional or historically accepted sense.
- 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_69e2ff2a2c088190be513727ee8bfe78 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620dc38088190b56b2b15ed75b3c2 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 18, 2026, 6:08 a.m.