Triple

T1187822
Position Surface form Disambiguated ID Type / Status
Subject Southern Bantu E25286 entity
Predicate hasMemberLanguage P7390 FINISHED
Object Kalanga
Kalanga is a Southern Bantu language spoken primarily in southwestern Zimbabwe and northeastern Botswana by the Kalanga people.
 E143249 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: Kalanga | Statement: [Southern Bantu, hasMemberLanguage, Kalanga]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kalanga
Context triple: [Southern Bantu, hasMemberLanguage, Kalanga]
  • A. Bongi
    Bongi is a neighborhood located in the city of Recife, in northeastern Brazil.
  • B. Nganasan
    The Nganasan are an Indigenous Samoyedic people of northern Siberia, traditionally semi-nomadic reindeer hunters and fishers with a distinct Uralic language and culture.
  • C. Mabalako
    Mabalako is a health zone in North Kivu Province in the eastern Democratic Republic of the Congo, known for being heavily affected by Ebola outbreaks.
  • D. Mandla
    Mandla is a town and administrative district headquarters in the central Indian state of Madhya Pradesh, known for its proximity to the Narmada River and nearby wildlife and forested areas.
  • E. Lilangeni
    The lilangeni is the official monetary unit of Eswatini, subdivided into 100 cents and commonly used alongside the South African rand.
  • 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: Kalanga
Triple: [Southern Bantu, hasMemberLanguage, Kalanga]
Generated description
Kalanga is a Southern Bantu language spoken primarily in southwestern Zimbabwe and northeastern Botswana by the Kalanga people.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kalanga
Target entity description: Kalanga is a Southern Bantu language spoken primarily in southwestern Zimbabwe and northeastern Botswana by the Kalanga people.
  • A. Bongi
    Bongi is a neighborhood located in the city of Recife, in northeastern Brazil.
  • B. Nganasan
    The Nganasan are an Indigenous Samoyedic people of northern Siberia, traditionally semi-nomadic reindeer hunters and fishers with a distinct Uralic language and culture.
  • C. Mabalako
    Mabalako is a health zone in North Kivu Province in the eastern Democratic Republic of the Congo, known for being heavily affected by Ebola outbreaks.
  • D. Mandla
    Mandla is a town and administrative district headquarters in the central Indian state of Madhya Pradesh, known for its proximity to the Narmada River and nearby wildlife and forested areas.
  • E. Lilangeni
    The lilangeni is the official monetary unit of Eswatini, subdivided into 100 cents and commonly used alongside the South African rand.
  • 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_69a49427d98881908646d6c63b8cea1e completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4bd568cf481908d10cf19a3ce28f3 completed March 1, 2026, 10:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac93b6343c8190af6e28ccdaab6562 completed March 7, 2026, 9:08 p.m.
NEDg Description generation batch_69ac9453f4488190a13ebabf3c8e07a5 completed March 7, 2026, 9:10 p.m.
NED2 Entity disambiguation (via description) batch_69ac952f74d48190b075919e0acd513d completed March 7, 2026, 9:14 p.m.
Created at: March 1, 2026, 7:45 p.m.