Triple

T6771296
Position Surface form Disambiguated ID Type / Status
Subject Baoulé language E155047 entity
Predicate hasDialects P4251 FINISHED
Object Asabu dialect
The Asabu dialect is a regional variety of the Baoulé language spoken by Baoulé communities in Côte d'Ivoire.
 E617316 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: Asabu dialect | Statement: [Baoulé language, hasDialects, Asabu dialect]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Asabu dialect
Context triple: [Baoulé language, hasDialects, Asabu dialect]
  • A. Doabi dialect
    The Doabi dialect is a regional variety of Punjabi traditionally spoken in the Doaba region of the Indian state of Punjab, between the Beas and Sutlej rivers.
  • B. Akusha dialect
    The Akusha dialect is a principal standardized variety of the Dargin language spoken in Dagestan, Russia.
  • C. Bajelani dialect
    The Bajelani dialect is a regional variety of the Gorani language spoken by Kurdish communities in parts of the Middle East.
  • D. Takbanuaz dialect
    The Takbanuaz dialect is a regional variety of the Bunun language spoken by an indigenous Bunun subgroup in Taiwan.
  • E. Nabua dialect
    The Nabua dialect is a local variety of the Rinconada Bikol language spoken primarily in and around the municipality of Nabua in Camarines Sur, Philippines.
  • 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: Asabu dialect
Triple: [Baoulé language, hasDialects, Asabu dialect]
Generated description
The Asabu dialect is a regional variety of the Baoulé language spoken by Baoulé communities in Côte d'Ivoire.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Asabu dialect
Target entity description: The Asabu dialect is a regional variety of the Baoulé language spoken by Baoulé communities in Côte d'Ivoire.
  • A. Doabi dialect
    The Doabi dialect is a regional variety of Punjabi traditionally spoken in the Doaba region of the Indian state of Punjab, between the Beas and Sutlej rivers.
  • B. Akusha dialect
    The Akusha dialect is a principal standardized variety of the Dargin language spoken in Dagestan, Russia.
  • C. Bajelani dialect
    The Bajelani dialect is a regional variety of the Gorani language spoken by Kurdish communities in parts of the Middle East.
  • D. Takbanuaz dialect
    The Takbanuaz dialect is a regional variety of the Bunun language spoken by an indigenous Bunun subgroup in Taiwan.
  • E. Nabua dialect
    The Nabua dialect is a local variety of the Rinconada Bikol language spoken primarily in and around the municipality of Nabua in Camarines Sur, Philippines.
  • 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_69c68812ef7c819099369f51febb725c completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d2496fa08190895d8b625fb0d699 completed March 27, 2026, 6:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69c712c46b70819097401afab991c808 completed March 27, 2026, 11:29 p.m.
NEDg Description generation batch_69c713853bf88190a8a07fd9f4ea1687 completed March 27, 2026, 11:32 p.m.
NED2 Entity disambiguation (via description) batch_69c713ead2a48190bbf95caf2ca8d997 completed March 27, 2026, 11:34 p.m.
Created at: March 27, 2026, 2:13 p.m.