Triple

T1187833
Position Surface form Disambiguated ID Type / Status
Subject Southern Bantu E25286 entity
Predicate hasMemberLanguage P7390 FINISHED
Object Ovambo
Ovambo is a Bantu language spoken primarily by the Ovambo people in northern Namibia and southern Angola.
 E143250 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: Ovambo | Statement: [Southern Bantu, hasMemberLanguage, Ovambo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Ovambo
Context triple: [Southern Bantu, hasMemberLanguage, Ovambo]
  • A. Lusiana
    Lusiana is a small town in the Veneto region of northern Italy, known as the birthplace of Indian politician Sonia Gandhi.
  • B. Okavango River
    The Okavango River is a major river in southwest Africa that famously fans out into the vast Okavango Delta, one of the world’s largest inland wetlands and a critical wildlife habitat.
  • C. Mvita
    Mvita is an alternative name for Kimvita, a historic Swahili settlement and cultural center on the coast of present-day Kenya.
  • D. Tamba
    Tamba is a city located in Hyogo Prefecture, Japan, known for its rural landscapes, traditional pottery, and historical sites.
  • E. Anseba
    Anseba is a central region of Eritrea known for its diverse ethnic communities, agriculture, and the regional capital Keren.
  • 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: Ovambo
Triple: [Southern Bantu, hasMemberLanguage, Ovambo]
Generated description
Ovambo is a Bantu language spoken primarily by the Ovambo people in northern Namibia and southern Angola.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Ovambo
Target entity description: Ovambo is a Bantu language spoken primarily by the Ovambo people in northern Namibia and southern Angola.
  • A. Lusiana
    Lusiana is a small town in the Veneto region of northern Italy, known as the birthplace of Indian politician Sonia Gandhi.
  • B. Okavango River
    The Okavango River is a major river in southwest Africa that famously fans out into the vast Okavango Delta, one of the world’s largest inland wetlands and a critical wildlife habitat.
  • C. Mvita
    Mvita is an alternative name for Kimvita, a historic Swahili settlement and cultural center on the coast of present-day Kenya.
  • D. Tamba
    Tamba is a city located in Hyogo Prefecture, Japan, known for its rural landscapes, traditional pottery, and historical sites.
  • E. Anseba
    Anseba is a central region of Eritrea known for its diverse ethnic communities, agriculture, and the regional capital Keren.
  • 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.