Triple
T19333395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rutul |
E483554
|
entity |
| Predicate | hasDialect |
P4251
|
FINISHED |
| Object | Mishlesh 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: Mishlesh dialect | Statement: [Rutul, hasDialect, Mishlesh dialect]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mishlesh dialect Context triple: [Rutul, hasDialect, Mishlesh dialect]
-
A.
Mishlesh dialect
chosen
The Mishlesh dialect is a regional variety of the Rutul language spoken by Rutul communities in the Caucasus.
-
B.
Malgwa dialect
The Malgwa dialect is a regional variety of the Mandara language spoken by communities in parts of northern Cameroon and neighboring areas.
-
C.
Mrass dialect
The Mrass dialect is a regional variety of the Shor language traditionally spoken by Shor communities along the Mrass River in southwestern Siberia.
-
D.
Intemelian dialect
The Intemelian dialect is a regional variety of the Ligurian language traditionally spoken around Ventimiglia and nearby coastal areas of northwestern Italy and southeastern France.
-
E.
Tlaisun dialect
The Tlaisun dialect is a regional variety of the Falam Chin language spoken by the Tlaisun community in parts of Chin State, Myanmar.
- 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.