Triple

T2566122
Position Surface form Disambiguated ID Type / Status
Subject Kikongo E57354 entity
Predicate hasDialect P4251 FINISHED
Object Kibembe
Kibembe is a Bantu language variety spoken in parts of Central Africa, recognized as one of the dialects of Kikongo.
 E281412 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: Kibembe | Statement: [Kikongo, hasDialect, Kibembe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kibembe
Context triple: [Kikongo, hasDialect, Kibembe]
  • A. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • B. Chitambo
    Chitambo is a historical locality in present-day Zambia best known as the place where Scottish explorer David Livingstone died in 1873.
  • C. Kiyombe
    Kiyombe is a regional variety of the Kikongo language spoken by communities in parts of Central Africa.
  • D. Kumba
    Kumba is a renowned steel roller coaster at Busch Gardens Tampa Bay, famous for its intense inversions and smooth, high-speed layout.
  • E. Tshiluba
    Tshiluba is a Bantu language widely spoken in south-central Democratic Republic of the Congo, particularly in the Kasai region.
  • 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: Kibembe
Triple: [Kikongo, hasDialect, Kibembe]
Generated description
Kibembe is a Bantu language variety spoken in parts of Central Africa, recognized as one of the dialects of Kikongo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kibembe
Target entity description: Kibembe is a Bantu language variety spoken in parts of Central Africa, recognized as one of the dialects of Kikongo.
  • A. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • B. Chitambo
    Chitambo is a historical locality in present-day Zambia best known as the place where Scottish explorer David Livingstone died in 1873.
  • C. Kiyombe chosen
    Kiyombe is a regional variety of the Kikongo language spoken by communities in parts of Central Africa.
  • D. Kumba
    Kumba is a renowned steel roller coaster at Busch Gardens Tampa Bay, famous for its intense inversions and smooth, high-speed layout.
  • E. Tshiluba
    Tshiluba is a Bantu language widely spoken in south-central Democratic Republic of the Congo, particularly in the Kasai region.
  • F. None of above.

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_69ab4a4ef9008190a0e6d4422b9418b7 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd35ef22c8190966612cc75f69eca completed March 7, 2026, 7:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69af906f488481909e5e45d8405022b5 completed March 10, 2026, 3:30 a.m.
NEDg Description generation batch_69af914ebc80819091524d1a4c316337 completed March 10, 2026, 3:34 a.m.
NED2 Entity disambiguation (via description) batch_69af91cc03648190936adfcccb6017de completed March 10, 2026, 3:36 a.m.
Created at: March 6, 2026, 9:48 p.m.