Triple
T32538370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Durma |
E831650
|
entity |
| Predicate | spokenDialectRegion |
P1762
|
FINISHED |
| Object | Najdi Arabic dialect area |
—
|
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: Najdi Arabic dialect area | Statement: [Durma, spokenDialectRegion, Najdi Arabic dialect area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spokenDialectRegion Context triple: [Durma, spokenDialectRegion, Najdi Arabic dialect area]
-
A.
regionalDialect
chosen
Indicates that one entity uses or is associated with a dialect specific to a particular geographic region in relation to another entity.
-
B.
spokenInCountryColloquialLanguage
Indicates that a language is informally or colloquially spoken within a particular country.
-
C.
motherTongueRegion
Indicates the geographic region where an entity’s native or primary language is predominantly spoken or originates.
-
D.
regionLanguage
Indicates that a particular language is used or officially recognized within a specific geographic region.
-
E.
recognizedRegionalLanguage
Indicates that a language holds officially recognized status within a specific region or subnational jurisdiction.
- 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_69f34924b1cc8190ad3aca0c0f012a7e |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c579194c819096d249335b3ccf6d |
completed | May 3, 2026, 3:48 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2a14b081908162923dfbf0a6f4 |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 1:01 a.m.