Triple

T7718569
Position Surface form Disambiguated ID Type / Status
Subject Emalahleni E174949 entity
Predicate formerName P65 FINISHED
Object Witbank
Witbank is a South African coal-mining city in Mpumalanga province, now officially known as Emalahleni.
E690178 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: Witbank | Statement: [Emalahleni, formerName, Witbank]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Witbank
Context triple: [Emalahleni, formerName, Witbank]
  • A. Rustenburg
    Rustenburg is a city in South Africa’s North West Province known for its mining industry and as one of the venues for the 2010 FIFA World Cup.
  • B. Randburg
    Randburg is a residential and commercial suburb in the north of Johannesburg, South Africa, known for its shopping centers, business districts, and leafy neighborhoods.
  • C. Bloemfontein
    Bloemfontein is a major South African city known as the seat of the country’s highest courts and one of its three national capitals.
  • D. Grahamstown
    Grahamstown is a historic university town in South Africa, renowned for its colonial-era architecture and the annual National Arts Festival.
  • E. Potchefstroom
    Potchefstroom is a historic university town in South Africa known for its academic institutions, military base, and role in the North West province’s agriculture and industry.
  • 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: Witbank
Triple: [Emalahleni, formerName, Witbank]
Generated description
Witbank is a South African coal-mining city in Mpumalanga province, now officially known as Emalahleni.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Witbank
Target entity description: Witbank is a South African coal-mining city in Mpumalanga province, now officially known as Emalahleni.
  • A. Rustenburg
    Rustenburg is a city in South Africa’s North West Province known for its mining industry and as one of the venues for the 2010 FIFA World Cup.
  • B. Randburg
    Randburg is a residential and commercial suburb in the north of Johannesburg, South Africa, known for its shopping centers, business districts, and leafy neighborhoods.
  • C. Bloemfontein
    Bloemfontein is a major South African city known as the seat of the country’s highest courts and one of its three national capitals.
  • D. Grahamstown
    Grahamstown is a historic university town in South Africa, renowned for its colonial-era architecture and the annual National Arts Festival.
  • E. Potchefstroom
    Potchefstroom is a historic university town in South Africa known for its academic institutions, military base, and role in the North West province’s agriculture and industry.
  • 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_69c6995c463c8190a14458036249d419 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c702ebb7448190ae8d47fe0cbb0907 completed March 27, 2026, 10:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69c91f4fb010819080ced464e4a71658 completed March 29, 2026, 12:47 p.m.
NEDg Description generation batch_69c91fb8cd088190bfc421a3ed8af920 completed March 29, 2026, 12:48 p.m.
NED2 Entity disambiguation (via description) batch_69c9205ce11c81909f8a760a17de6dd9 completed March 29, 2026, 12:51 p.m.
Created at: March 27, 2026, 4:05 p.m.