Triple

T9509827
Position Surface form Disambiguated ID Type / Status
Subject Ugu District Municipality E229363 entity
Predicate includesTown P847 FINISHED
Object Umtentweni E218868 NE FINISHED

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: Umtentweni | Statement: [Ugu District Municipality, includesTown, Umtentweni]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Umtentweni
Context triple: [Ugu District Municipality, includesTown, Umtentweni]
  • A. Umtentweni chosen
    Umtentweni is a coastal resort town on South Africa’s KwaZulu-Natal South Coast, known for its beaches, subtropical climate, and relaxed holiday atmosphere.
  • B. Mzuzu
    Mzuzu is a major city in northern Malawi known as an important commercial and administrative center for the region.
  • C. Makoni
    Makoni is a town in Zimbabwe’s Manicaland Province, known primarily as a local administrative and commercial center for the surrounding rural district.
  • D. Umtata
    Umtata is the former name of Mthatha, a town in South Africa’s Eastern Cape that serves as a regional economic and administrative center.
  • E. Tembisa
    Tembisa is a large township in Gauteng, South Africa, situated on the East Rand and known as a densely populated residential area within the City of Ekurhuleni.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca847611c48190a28c028644198c75 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9857058881909e0a40e2024a7b4c completed April 1, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69d13a31600c8190a4a7ecb5231caa36 completed April 4, 2026, 4:20 p.m.
Created at: March 30, 2026, 7:58 p.m.