Triple

T654892
Position Surface form Disambiguated ID Type / Status
Subject Masvingo E11625 entity
Predicate formerName P65 FINISHED
Object Nyanda
Nyanda is the former name of Masvingo, a historic city in southeastern Zimbabwe known for its proximity to the Great Zimbabwe ruins.
 E85980 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: Nyanda | Statement: [Masvingo, formerName, Nyanda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nyanda
Context triple: [Masvingo, formerName, Nyanda]
  • A. Yenda
    Yenda is a small rural town in the Riverina region of New South Wales, Australia, known for its agricultural production, particularly viticulture and horticulture.
  • B. Murambi
    Murambi is a residential suburb of Mutare, a major city in eastern Zimbabwe.
  • C. Ndowe
    Ndowe is a Bantu language spoken by the Ndowe people along the coastal region of Equatorial Guinea.
  • D. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • 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: Nyanda
Triple: [Masvingo, formerName, Nyanda]
Generated description
Nyanda is the former name of Masvingo, a historic city in southeastern Zimbabwe known for its proximity to the Great Zimbabwe ruins.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nyanda
Target entity description: Nyanda is the former name of Masvingo, a historic city in southeastern Zimbabwe known for its proximity to the Great Zimbabwe ruins.
  • A. Yenda
    Yenda is a small rural town in the Riverina region of New South Wales, Australia, known for its agricultural production, particularly viticulture and horticulture.
  • B. Murambi
    Murambi is a residential suburb of Mutare, a major city in eastern Zimbabwe.
  • C. Ndowe
    Ndowe is a Bantu language spoken by the Ndowe people along the coastal region of Equatorial Guinea.
  • D. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • 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_69a4932862a0819098be659c814e4981 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49f4bb5b881908a18b5ec1c94e0cf completed March 1, 2026, 8:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69a637452b0c8190a1e82989f20e68db completed March 3, 2026, 1:20 a.m.
NEDg Description generation batch_69a6386ab4548190906002f853637d02 completed March 3, 2026, 1:24 a.m.
NED2 Entity disambiguation (via description) batch_69a638cef5e881909830afa5d1e1818e completed March 3, 2026, 1:26 a.m.
Created at: March 1, 2026, 7:36 p.m.