Triple
T25911660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cala Bona |
E652910
|
entity |
| Predicate | hasLocalVariantLanguage |
P5595
|
FINISHED |
| Object | Mallorquí (Mallorcan Catalan) |
—
|
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: Mallorquí (Mallorcan Catalan) | Statement: [Cala Bona, hasLocalVariantLanguage, Mallorquí (Mallorcan Catalan)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalVariantLanguage Context triple: [Cala Bona, hasLocalVariantLanguage, Mallorquí (Mallorcan Catalan)]
-
A.
usesLocalLanguageVariant
Indicates that an entity employs a region-specific or localized form of a language rather than a standard or global variant.
-
B.
languageVariant
chosen
Indicates that one language is a variant, dialect, or localized form of another language.
-
C.
hasLinguisticVariety
Indicates that one entity possesses or exhibits a particular linguistic variety in relation to another entity or context.
-
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.
labelLanguageVariant
Indicates that one label is a language-specific variant or localized form of another label.
- 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_69e7ab3d3f8481909bc53ed64c06af33 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f69edbb7648190bd89c57e0932eac1 |
completed | May 3, 2026, 1:03 a.m. |
| PD | Predicate disambiguation | batch_69f69d17e8d48190b30bcc2f4bd81eb2 |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 22, 2026, 8:28 a.m.