Triple

T33844907
Position Surface form Disambiguated ID Type / Status
Subject Marondera District E867452 entity
Predicate governingBody P46 FINISHED
Object Marondera Rural District Council
Marondera Rural District Council is the local government authority responsible for administering and providing services to the rural areas of Marondera District in Zimbabwe.
E2070141 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: Marondera Rural District Council | Statement: [Marondera District, governingBody, Marondera Rural District Council]
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: Marondera Rural District Council
Triple: [Marondera District, governingBody, Marondera Rural District Council]
Generated description
Marondera Rural District Council is the local government authority responsible for administering and providing services to the rural areas of Marondera District in Zimbabwe.

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_69f349937b648190a34ada70f6a2b534 completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f7005230ac81908b3a725b88112a83 completed May 3, 2026, 7:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a366eb1b49881908d3c0c5904d30fd3 completed June 20, 2026, 10:42 a.m.
NEDg Description generation batch_6a366f86630c81908530464a68656b76 completed June 20, 2026, 10:46 a.m.
NED2 Entity disambiguation (via description) batch_6a3671039b748190a4dd9ccda7446e01 completed June 20, 2026, 10:52 a.m.
Created at: May 1, 2026, 1:47 a.m.