Triple

T22047218
Position Surface form Disambiguated ID Type / Status
Subject Umlazi E544792 entity
Predicate near P350 FINISHED
Object Isipingo NE NERFINISHED

How this triple was built (2 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: Isipingo | Statement: [Umlazi, near, Isipingo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Isipingo
Context triple: [Umlazi, near, Isipingo]
  • A. Isipingo chosen
    Isipingo is a coastal town in KwaZulu-Natal, South Africa, situated just south of Durban and known for its industrial zones and residential suburbs.
  • B. Ngumbi
    Ngumbi is a Bantu language spoken along the central coast of Cameroon, closely related to and sometimes considered a variety of Kombe.
  • C. Bolongongo
    Bolongongo is a town and municipality located in Angola’s Cuanza Norte Province.
  • D. Empangeni
    Empangeni is a town in KwaZulu-Natal, South Africa, situated near Richards Bay and known as a regional commercial and service center.
  • E. Chipinga
    Chipinga is the former name of Chipinge, a town in southeastern Zimbabwe known for its agriculture and proximity to the Mozambique border.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e32445c8190ab97089b48a130bb completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f12830c674819080254d77ee02bc9f completed April 28, 2026, 9:35 p.m.
Created at: April 16, 2026, 8:26 p.m.