Triple
T23310120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adyghe language |
E590558
|
entity |
| Predicate | standardBasedOn |
P1587
|
FINISHED |
| Object | Temirgoy dialect |
—
|
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: Temirgoy dialect | Statement: [Adyghe language, standardBasedOn, Temirgoy dialect]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Temirgoy dialect Context triple: [Adyghe language, standardBasedOn, Temirgoy dialect]
-
A.
Temirgoy dialect
chosen
The Temirgoy dialect is a major variety of the Adyghe (Circassian) language traditionally spoken by the Temirgoy subgroup of the Circassian people.
-
B.
Kyzyl dialect
The Kyzyl dialect is a regional variety of the Khakas language spoken by Khakas communities in parts of Siberia, Russia.
-
C.
Saryk dialect
The Saryk dialect is a regional variety of the Turkmen language traditionally spoken by the Saryk Turkmen people of Central Asia.
-
D.
Buynaksk dialect
The Buynaksk dialect is a regional variety of the Kumyk language spoken around the city of Buynaksk in Dagestan, Russia.
-
E.
Göklen dialect
The Göklen dialect is a regional variety of the Turkmen language traditionally spoken by the Göklen Turkmen people of northeastern Iran and surrounding areas.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e25d1d32188190948eb76909d1dcc3 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1972acad08190bb56541b822555cd |
completed | April 29, 2026, 5:29 a.m. |
Created at: April 17, 2026, 5:05 p.m.