Triple

T31238687
Position Surface form Disambiguated ID Type / Status
Subject Ugu District E796497 entity
Predicate contains P35 FINISHED
Object Vulamehlo Local Municipality
Vulamehlo Local Municipality was a former local municipality in the KwaZulu-Natal province of South Africa, situated within the predominantly rural Ugu District and encompassing several small towns and villages.
E2285856 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: Vulamehlo Local Municipality | Statement: [Ugu District, contains, Vulamehlo Local Municipality]
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: Vulamehlo Local Municipality
Triple: [Ugu District, contains, Vulamehlo Local Municipality]
Generated description
Vulamehlo Local Municipality was a former local municipality in the KwaZulu-Natal province of South Africa, situated within the predominantly rural Ugu District and encompassing several small towns and villages.

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_69f224db69ac81909a370adad6a7ac7c completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69d23fb08819094259d05e14813fd completed May 3, 2026, 12:56 a.m.
NED1 Entity disambiguation (via context triple) batch_6a46295133648190aa2941eddcfed41e completed July 2, 2026, 9:03 a.m.
NEDg Description generation batch_6a462a3f18348190bc1eeb5af88330f4 completed July 2, 2026, 9:07 a.m.
NED2 Entity disambiguation (via description) batch_6a46300bca408190a9324196b6deeabd completed July 2, 2026, 9:31 a.m.
Created at: April 29, 2026, 9:11 p.m.