Triple
T19333396
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rutul |
E483554
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object | Khnov 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: Khnov dialect | Statement: [Rutul, hasDialect, Khnov dialect]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Khnov dialect Context triple: [Rutul, hasDialect, Khnov dialect]
-
A.
Borch-Khnov dialect
chosen
The Borch-Khnov dialect is a regional variety of the Rutul language spoken by Rutul communities in parts of the eastern Caucasus.
-
B.
Kachinsky dialect
The Kachinsky dialect is a regional variety of the Khakas language spoken by Khakas communities in parts of Siberia.
-
C.
Kamenskoye dialect
The Kamenskoye dialect is a regional variety of the Koryak language traditionally spoken by Koryak communities in the Kamenskoye area of Russia’s Far East.
-
D.
Sagaysky dialect
The Sagaysky dialect is a regional variety of the Khakas language spoken by the Sagay subgroup of the Khakas people in Siberia.
-
E.
Aknogai dialect
The Aknogai dialect is a regional variety of the Nogai language spoken by Nogai communities in the North Caucasus.
- 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_69d8e8d13e3c81909d91d1d5ec37c095 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e61642f49c81909226cfd701f7c139 |
completed | April 20, 2026, 12:04 p.m. |
Created at: April 10, 2026, 1:33 p.m.