Triple

T1187827
Position Surface form Disambiguated ID Type / Status
Subject Southern Bantu E25286 entity
Predicate hasMemberLanguage P7390 FINISHED
Object Nyanja
Nyanja is a major Bantu language spoken primarily in Malawi, Zambia, Mozambique, and Zimbabwe, known for serving as a lingua franca in parts of southern Africa.
 E136466 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: Nyanja | Statement: [Southern Bantu, hasMemberLanguage, Nyanja]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nyanja
Context triple: [Southern Bantu, hasMemberLanguage, Nyanja]
  • A. Kigoma
    Kigoma is a port city in western Tanzania located on the eastern shore of Lake Tanganyika and serving as a key regional transport and trade hub.
  • B. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • C. Tshiluba
    Tshiluba is a Bantu language widely spoken in south-central Democratic Republic of the Congo, particularly in the Kasai region.
  • D. Uvinza
    Uvinza is a town in western Tanzania known historically for its salt production and location along the Central Line railway in Kigoma Region.
  • E. Arusha, Tanzania
    Arusha, Tanzania is a major city in northern Tanzania known as a diplomatic hub and gateway to popular safari destinations and Mount Kilimanjaro.
  • 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: Nyanja
Triple: [Southern Bantu, hasMemberLanguage, Nyanja]
Generated description
Nyanja is a major Bantu language spoken primarily in Malawi, Zambia, Mozambique, and Zimbabwe, known for serving as a lingua franca in parts of southern Africa.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nyanja
Target entity description: Nyanja is a major Bantu language spoken primarily in Malawi, Zambia, Mozambique, and Zimbabwe, known for serving as a lingua franca in parts of southern Africa.
  • A. Kigoma
    Kigoma is a port city in western Tanzania located on the eastern shore of Lake Tanganyika and serving as a key regional transport and trade hub.
  • B. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • C. Tshiluba
    Tshiluba is a Bantu language widely spoken in south-central Democratic Republic of the Congo, particularly in the Kasai region.
  • D. Uvinza
    Uvinza is a town in western Tanzania known historically for its salt production and location along the Central Line railway in Kigoma Region.
  • E. Arusha, Tanzania
    Arusha, Tanzania is a major city in northern Tanzania known as a diplomatic hub and gateway to popular safari destinations and Mount Kilimanjaro.
  • 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_69ac764a5f508190a54c8f01cf0b0d11 completed March 7, 2026, 7:02 p.m.
NEDg Description generation batch_69ac76c0863c81909c68208709e4767b completed March 7, 2026, 7:04 p.m.
NED2 Entity disambiguation (via description) batch_69ac778551f88190ac041d80e41d209d completed March 7, 2026, 7:07 p.m.
Created at: March 1, 2026, 7:45 p.m.