Triple

T6472583
Position Surface form Disambiguated ID Type / Status
Subject Mopani District Municipality E145990 entity
Predicate seat P75 FINISHED
Object Giyani
Giyani is a town in northeastern Limpopo, South Africa, known as an administrative and commercial center for the surrounding rural region.
E611309 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: Giyani | Statement: [Mopani District Municipality, seat, Giyani]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Giyani
Context triple: [Mopani District Municipality, seat, Giyani]
  • A. Mogoditshane
    Mogoditshane is a rapidly growing suburban township located just outside Botswana’s capital, Gaborone.
  • B. Makhado
    Makhado is a major town in South Africa’s Limpopo province, serving as an important commercial and administrative center in the Vhembe region.
  • C. Polokwane
    Polokwane is a city in South Africa’s Limpopo province that served as one of the venues for matches during the 2010 FIFA World Cup.
  • D. 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.
  • E. Masandawana
    Masandawana is the popular nickname of South African football club Mamelodi Sundowns F.C., one of the country’s most successful and widely supported teams.
  • 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: Giyani
Triple: [Mopani District Municipality, seat, Giyani]
Generated description
Giyani is a town in northeastern Limpopo, South Africa, known as an administrative and commercial center for the surrounding rural region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Giyani
Target entity description: Giyani is a town in northeastern Limpopo, South Africa, known as an administrative and commercial center for the surrounding rural region.
  • A. Mogoditshane
    Mogoditshane is a rapidly growing suburban township located just outside Botswana’s capital, Gaborone.
  • B. Makhado
    Makhado is a major town in South Africa’s Limpopo province, serving as an important commercial and administrative center in the Vhembe region.
  • C. Polokwane
    Polokwane is a city in South Africa’s Limpopo province that served as one of the venues for matches during the 2010 FIFA World Cup.
  • D. 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.
  • E. Masandawana
    Masandawana is the popular nickname of South African football club Mamelodi Sundowns F.C., one of the country’s most successful and widely supported teams.
  • 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_69c008fec7408190af7b146dc63d9750 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a3188488190a1b7452ede91ba5e completed March 22, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6f77d46c081908bbbd0be951cb44f completed March 27, 2026, 9:32 p.m.
NEDg Description generation batch_69c6f8453af88190b237c249bfbb4f8c completed March 27, 2026, 9:36 p.m.
NED2 Entity disambiguation (via description) batch_69c6f8d5630c8190913e8572a70b82c1 completed March 27, 2026, 9:38 p.m.
Created at: March 22, 2026, 4:50 p.m.