Triple

T2566117
Position Surface form Disambiguated ID Type / Status
Subject Kikongo E57354 entity
Predicate hasDialect P4251 FINISHED
Object Kiyombe
Kiyombe is a regional variety of the Kikongo language spoken by communities in parts of Central Africa.
 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: Kiyombe | Statement: [Kikongo, hasDialect, Kiyombe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kiyombe
Context triple: [Kikongo, hasDialect, Kiyombe]
  • A. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • B. Nyokum
    Nyokum is a major agricultural and religious festival of the Nyishi tribe in Arunachal Pradesh, India, celebrated to invoke prosperity, harmony, and good harvest.
  • C. Urambo
    Urambo is a town and district headquarters in western Tanzania known historically for tobacco production and its location within the Tabora Region.
  • D. Murambi
    Murambi is a residential suburb of Mutare, a major city in eastern Zimbabwe.
  • E. Negombo
    Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
  • 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: Kiyombe
Triple: [Kikongo, hasDialect, Kiyombe]
Generated description
Kiyombe is a regional variety of the Kikongo language spoken by communities in parts of Central Africa.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kiyombe
Target entity description: Kiyombe is a regional variety of the Kikongo language spoken by communities in parts of Central Africa.
  • A. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • B. Nyokum
    Nyokum is a major agricultural and religious festival of the Nyishi tribe in Arunachal Pradesh, India, celebrated to invoke prosperity, harmony, and good harvest.
  • C. Urambo
    Urambo is a town and district headquarters in western Tanzania known historically for tobacco production and its location within the Tabora Region.
  • D. Murambi
    Murambi is a residential suburb of Mutare, a major city in eastern Zimbabwe.
  • E. Negombo
    Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
  • 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_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_69af83a4f6788190be268076838711df completed March 10, 2026, 2:36 a.m.
NEDg Description generation batch_69af84d26eb48190b982441a0a63ccda completed March 10, 2026, 2:41 a.m.
NED2 Entity disambiguation (via description) batch_69af858561f48190b7a2863d733a1b13 completed March 10, 2026, 2:44 a.m.
Created at: March 6, 2026, 9:48 p.m.