Triple
T18713529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cassis |
E457576
|
entity |
| Predicate | traditionalRegionalLanguage |
P1762
|
FINISHED |
| Object | Provençal Occitan |
—
|
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: Provençal Occitan | Statement: [Cassis, traditionalRegionalLanguage, Provençal Occitan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalRegionalLanguage Context triple: [Cassis, traditionalRegionalLanguage, Provençal Occitan]
-
A.
traditionalLanguageName
Indicates the name traditionally used in a particular language to refer to the subject entity.
-
B.
regionLanguage
Indicates that a particular language is used or officially recognized within a specific geographic region.
-
C.
recognizedRegionalLanguage
Indicates that a language holds officially recognized status within a specific region or subnational jurisdiction.
-
D.
regionalDialect
chosen
Indicates that one entity uses or is associated with a dialect specific to a particular geographic region in relation to another entity.
-
E.
languageFamilyTraditional
Indicates that one entity belongs to, or is classified under, the traditional language family of the other entity.
- 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_69d8d392aad081909fe31aa03e6e97d1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56ab352b481909b444e7c476898f4 |
completed | April 19, 2026, 11:52 p.m. |
| PD | Predicate disambiguation | batch_69e478e0889c8190a118d67b200ce8ef |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:50 a.m.