Triple

T3111866
Position Surface form Disambiguated ID Type / Status
Subject Manicaland Province E64969 entity
Predicate hasTown P847 FINISHED
Object Makoni
Makoni is a town in Zimbabwe’s Manicaland Province, known primarily as a local administrative and commercial center for the surrounding rural district.
 E328808 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: Makoni | Statement: [Manicaland Province, hasTown, Makoni]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Makoni
Context triple: [Manicaland Province, hasTown, Makoni]
  • A. Mzuzu
    Mzuzu is a major city in northern Malawi known as an important commercial and administrative center for the region.
  • B. Mpondo
    The Mpondo are a Southern African ethnic group closely related to the Xhosa, known for their distinct language variety, cultural traditions, and historical kingdom in what is now South Africa’s Eastern Cape.
  • C. Nkayi
    Nkayi is a rural district and its main town in western Zimbabwe, situated in Matabeleland North Province and known for its predominantly Ndebele-speaking communities and subsistence agriculture.
  • D. Lomwe
    Lomwe is a Bantu language spoken primarily in Mozambique and Malawi by the Lomwe people.
  • E. Bongi
    Bongi is a neighborhood located in the city of Recife, in northeastern Brazil.
  • 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: Makoni
Triple: [Manicaland Province, hasTown, Makoni]
Generated description
Makoni is a town in Zimbabwe’s Manicaland Province, known primarily as a local administrative and commercial center for the surrounding rural district.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Makoni
Target entity description: Makoni is a town in Zimbabwe’s Manicaland Province, known primarily as a local administrative and commercial center for the surrounding rural district.
  • A. Mzuzu
    Mzuzu is a major city in northern Malawi known as an important commercial and administrative center for the region.
  • B. Mpondo
    The Mpondo are a Southern African ethnic group closely related to the Xhosa, known for their distinct language variety, cultural traditions, and historical kingdom in what is now South Africa’s Eastern Cape.
  • C. Nkayi
    Nkayi is a rural district and its main town in western Zimbabwe, situated in Matabeleland North Province and known for its predominantly Ndebele-speaking communities and subsistence agriculture.
  • D. Lomwe
    Lomwe is a Bantu language spoken primarily in Mozambique and Malawi by the Lomwe people.
  • E. Bongi
    Bongi is a neighborhood located in the city of Recife, in northeastern Brazil.
  • 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_69ad857eeaf48190b34ebfdaa7a264cf completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada43b0b3c8190a828c9cfcf730ed9 completed March 8, 2026, 4:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69b20f5cfc7c8190b867794c0e9a271e completed March 12, 2026, 12:57 a.m.
NEDg Description generation batch_69b2101824c0819097dc967d83d18751 completed March 12, 2026, 1 a.m.
NED2 Entity disambiguation (via description) batch_69b210886d308190b120beb8f6bcbf3a completed March 12, 2026, 1:02 a.m.
Created at: March 8, 2026, 3:04 p.m.