Triple
T20899314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khakas language |
E514627
|
entity |
| Predicate | hasDialects |
P4251
|
FINISHED |
| Object |
Kyzyl dialect
The Kyzyl dialect is a regional variety of the Khakas language spoken by Khakas communities in parts of Siberia, Russia.
|
E1457244
|
NE FINISHED |
How this triple was built (4 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: Kyzyl dialect | Statement: [Khakas language, hasDialects, Kyzyl dialect]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kyzyl dialect Context triple: [Khakas language, hasDialects, Kyzyl dialect]
-
A.
Saryk dialect
The Saryk dialect is a regional variety of the Turkmen language traditionally spoken by the Saryk Turkmen people of Central Asia.
-
B.
Buynaksk dialect
The Buynaksk dialect is a regional variety of the Kumyk language spoken around the city of Buynaksk in Dagestan, Russia.
-
C.
Khunzakh dialect
The Khunzakh dialect is a regional variety of the Avar language spoken in and around the village of Khunzakh in Dagestan, Russia.
-
D.
Khoshut dialect
The Khoshut dialect is a regional variety of the Oirat Mongolic language traditionally spoken by the Khoshut people of Central Asia.
-
E.
Oroqen dialect
The Oroqen dialect is a regional variety of the Tungusic Evenki language spoken primarily by the Oroqen people of northeastern China.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Kyzyl dialect Triple: [Khakas language, hasDialects, Kyzyl dialect]
Generated description
The Kyzyl dialect is a regional variety of the Khakas language spoken by Khakas communities in parts of Siberia, Russia.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kyzyl dialect Target entity description: The Kyzyl dialect is a regional variety of the Khakas language spoken by Khakas communities in parts of Siberia, Russia.
-
A.
Saryk dialect
The Saryk dialect is a regional variety of the Turkmen language traditionally spoken by the Saryk Turkmen people of Central Asia.
-
B.
Buynaksk dialect
The Buynaksk dialect is a regional variety of the Kumyk language spoken around the city of Buynaksk in Dagestan, Russia.
-
C.
Khunzakh dialect
The Khunzakh dialect is a regional variety of the Avar language spoken in and around the village of Khunzakh in Dagestan, Russia.
-
D.
Khoshut dialect
The Khoshut dialect is a regional variety of the Oirat Mongolic language traditionally spoken by the Khoshut people of Central Asia.
-
E.
Oroqen dialect
The Oroqen dialect is a regional variety of the Tungusic Evenki language spoken primarily by the Oroqen people of northeastern China.
- F. None of above. chosen
Provenance (5 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_69e0b4f8a1108190bce3d31331290ced |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6e8f92bd88190b59b2131ad1d9aa1 |
completed | April 21, 2026, 3:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0918cefa2081909768f9923a96f209 |
completed | May 17, 2026, 1:24 a.m. |
| NEDg | Description generation | batch_6a091ca90e788190bb74c161c9233634 |
completed | May 17, 2026, 1:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a091d9402448190bb223e0950450e4e |
completed | May 17, 2026, 1:44 a.m. |
Created at: April 16, 2026, 12:47 p.m.