Triple

T9669411
Position Surface form Disambiguated ID Type / Status
Subject Khakas E233987 entity
Predicate hasDialect P4251 FINISHED
Object Kachinsky dialect
The Kachinsky dialect is a regional variety of the Khakas language spoken by Khakas communities in parts of Siberia.
 E814616 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: Kachinsky dialect | Statement: [Khakas, hasDialect, Kachinsky dialect]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kachinsky dialect
Context triple: [Khakas, hasDialect, Kachinsky dialect]
  • A. Sagaysky dialect
    The Sagaysky dialect is a regional variety of the Khakas language spoken by the Sagay subgroup of the Khakas people in Siberia.
  • B. Babolki dialect
    The Babolki dialect is a regional variety of the Mazanderani language traditionally spoken around the city of Babol in northern Iran.
  • C. Krakolye dialect
    The Krakolye dialect is a regional variety of the Votic language traditionally spoken in and around the village of Krakolye in Ingria.
  • D. Gaika dialect
    The Gaika dialect is a regional variety of the Xhosa language traditionally associated with the amaGqika subgroup in South Africa.
  • 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. 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: Kachinsky dialect
Triple: [Khakas, hasDialect, Kachinsky dialect]
Generated description
The Kachinsky dialect is a regional variety of the Khakas language spoken by Khakas communities in parts of Siberia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kachinsky dialect
Target entity description: The Kachinsky dialect is a regional variety of the Khakas language spoken by Khakas communities in parts of Siberia.
  • A. Sagaysky dialect
    The Sagaysky dialect is a regional variety of the Khakas language spoken by the Sagay subgroup of the Khakas people in Siberia.
  • B. Babolki dialect
    The Babolki dialect is a regional variety of the Mazanderani language traditionally spoken around the city of Babol in northern Iran.
  • C. Krakolye dialect
    The Krakolye dialect is a regional variety of the Votic language traditionally spoken in and around the village of Krakolye in Ingria.
  • D. Gaika dialect
    The Gaika dialect is a regional variety of the Xhosa language traditionally associated with the amaGqika subgroup in South Africa.
  • 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. 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_69ca848f55e48190b3f67252571c3d45 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9c3d5b3481908c8c66a3528875aa completed April 1, 2026, 10:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69d190f691c8819093fe133bdbe1c9d1 completed April 4, 2026, 10:30 p.m.
NEDg Description generation batch_69d1919b536481908fe80426c9aa6443 completed April 4, 2026, 10:32 p.m.
NED2 Entity disambiguation (via description) batch_69d191ca17b8819097750a7b638aee72 completed April 4, 2026, 10:33 p.m.
Created at: March 30, 2026, 8:15 p.m.