Triple

T6753772
Position Surface form Disambiguated ID Type / Status
Subject Sara language E154401 entity
Predicate hasDialect P4251 FINISHED
Object Mbay
Mbay is a Central Sudanic language spoken primarily in Chad and the Central African Republic, known for its complex tonal system and noun class distinctions.
 E615473 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: Mbay | Statement: [Sara language, hasDialect, Mbay]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mbay
Context triple: [Sara language, hasDialect, Mbay]
  • A. Mbengwi
    Mbengwi is a town in western Cameroon that serves as the administrative center of Momo Division in the country's Northwest Region.
  • B. Mbouda
    Mbouda is a significant urban center in western Cameroon known for its role as a commercial and administrative hub in the region.
  • C. Eyamba
    Eyamba is a prominent clan of the Efik people of southeastern Nigeria, historically associated with leadership and influence in the Old Calabar region.
  • D. Oshikwambi
    Oshikwambi is a regional dialect of the Oshiwambo language spoken by the Kwambi people in northern Namibia.
  • E. Mbini
    Mbini is a town in mainland Equatorial Guinea situated along the Benito River, known historically as a small river port and local administrative center.
  • 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: Mbay
Triple: [Sara language, hasDialect, Mbay]
Generated description
Mbay is a Central Sudanic language spoken primarily in Chad and the Central African Republic, known for its complex tonal system and noun class distinctions.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mbay
Target entity description: Mbay is a Central Sudanic language spoken primarily in Chad and the Central African Republic, known for its complex tonal system and noun class distinctions.
  • A. Mbengwi
    Mbengwi is a town in western Cameroon that serves as the administrative center of Momo Division in the country's Northwest Region.
  • B. Mbouda
    Mbouda is a significant urban center in western Cameroon known for its role as a commercial and administrative hub in the region.
  • C. Eyamba
    Eyamba is a prominent clan of the Efik people of southeastern Nigeria, historically associated with leadership and influence in the Old Calabar region.
  • D. Oshikwambi
    Oshikwambi is a regional dialect of the Oshiwambo language spoken by the Kwambi people in northern Namibia.
  • E. Mbini
    Mbini is a town in mainland Equatorial Guinea situated along the Benito River, known historically as a small river port and local administrative center.
  • 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_69c6880fd5808190be684854081e27dd completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d1f32fa08190bb23dc24fef14c8d completed March 27, 2026, 6:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69c70b1c4594819084716e21b16191e3 completed March 27, 2026, 10:56 p.m.
NEDg Description generation batch_69c70c4111848190906b0e43cf4ae325 completed March 27, 2026, 11:01 p.m.
NED2 Entity disambiguation (via description) batch_69c70cbb8644819091a8a9c061dfd605 completed March 27, 2026, 11:03 p.m.
Created at: March 27, 2026, 2:11 p.m.