Triple

T24918604
Position Surface form Disambiguated ID Type / Status
Subject Nkayi Rural District Council E624058 entity
Predicate locatedIn P40 FINISHED
Object Nkayi District
Nkayi District is an administrative district in Matabeleland North Province of Zimbabwe, encompassing rural communities governed by the Nkayi Rural District Council.
E1708137 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: Nkayi District | Statement: [Nkayi Rural District Council, locatedIn, Nkayi District]
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: Nkayi District
Triple: [Nkayi Rural District Council, locatedIn, Nkayi District]
Generated description
Nkayi District is an administrative district in Matabeleland North Province of Zimbabwe, encompassing rural communities governed by the Nkayi Rural District Council.

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_69e2fac889c081908e9ff686cb428e5a completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f4238e43c08190be03e813b8cdfe28 completed May 1, 2026, 3:52 a.m.
NED1 Entity disambiguation (via context triple) batch_6a111adc3d048190878d6190200042b1 completed May 23, 2026, 3:11 a.m.
NEDg Description generation batch_6a111c0a65f881908a29d01412627de9 completed May 23, 2026, 3:16 a.m.
NED2 Entity disambiguation (via description) batch_6a111ca03b088190937f673d972fdca2 completed May 23, 2026, 3:18 a.m.
Created at: April 18, 2026, 5:28 a.m.