Triple

T5614601
Position Surface form Disambiguated ID Type / Status
Subject Lomwe E147444 entity
Predicate hasNeighboringLanguage P16383 FINISHED
Object Makonde
Makonde is a Bantu language spoken primarily by the Makonde people of northern Mozambique and southern Tanzania.
 E534696 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: Makonde | Statement: [Lomwe, hasNeighboringLanguage, Makonde]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Makonde
Context triple: [Lomwe, hasNeighboringLanguage, Makonde]
  • A. Tshimanda
    Tshimanda is a regional dialect of the Tshivenda language spoken by a specific community of Venda people in South Africa.
  • B. Oshindali
    Oshindali is a regional dialect of the Oshiwambo language spoken primarily by communities in northern Namibia and southern Angola.
  • C. Masisi
    Masisi is a town in the eastern Democratic Republic of the Congo, situated in the conflict-affected, mineral-rich highlands of North Kivu Province.
  • D. Matsigenka
    The Matsigenka are an Indigenous people of the Peruvian Amazon known for their forest-based subsistence lifestyle, distinct language, and rich shamanic and cosmological traditions.
  • E. Mpulungu
    Mpulungu is a Zambian port town that serves as the country’s main access point to Lake Tanganyika and a hub for regional fishing and trade.
  • 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: Makonde
Triple: [Lomwe, hasNeighboringLanguage, Makonde]
Generated description
Makonde is a Bantu language spoken primarily by the Makonde people of northern Mozambique and southern Tanzania.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Makonde
Target entity description: Makonde is a Bantu language spoken primarily by the Makonde people of northern Mozambique and southern Tanzania.
  • A. Tshimanda
    Tshimanda is a regional dialect of the Tshivenda language spoken by a specific community of Venda people in South Africa.
  • B. Oshindali
    Oshindali is a regional dialect of the Oshiwambo language spoken primarily by communities in northern Namibia and southern Angola.
  • C. Masisi
    Masisi is a town in the eastern Democratic Republic of the Congo, situated in the conflict-affected, mineral-rich highlands of North Kivu Province.
  • D. Matsigenka
    The Matsigenka are an Indigenous people of the Peruvian Amazon known for their forest-based subsistence lifestyle, distinct language, and rich shamanic and cosmological traditions.
  • E. Mpulungu
    Mpulungu is a Zambian port town that serves as the country’s main access point to Lake Tanganyika and a hub for regional fishing and trade.
  • 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_69c00905d4588190bd967842bbcf2219 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c02123fa9081909086c9cce3f3e907 completed March 22, 2026, 5:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69c04d51c12c8190911fb9a0c0d234d8 completed March 22, 2026, 8:13 p.m.
NEDg Description generation batch_69c04e89b7c481908abae227d22cc814 completed March 22, 2026, 8:18 p.m.
NED2 Entity disambiguation (via description) batch_69c04f41b158819097f9ef536215e248 completed March 22, 2026, 8:21 p.m.
Created at: March 22, 2026, 3:39 p.m.