Triple

T38331883
Position Surface form Disambiguated ID Type / Status
Subject Kilgoris Constituency E1037843 entity
Predicate partOfElectoralRegion P9851 FINISHED
Object Narok County constituencies
Narok County constituencies are the electoral areas within Narok County, Kenya, each represented by a Member of Parliament in the National Assembly.
E2266867 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: Narok County constituencies | Statement: [Kilgoris Constituency, partOfElectoralRegion, Narok County constituencies]
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: Narok County constituencies
Triple: [Kilgoris Constituency, partOfElectoralRegion, Narok County constituencies]
Generated description
Narok County constituencies are the electoral areas within Narok County, Kenya, each represented by a Member of Parliament in the National Assembly.

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_69f76e20d65c81909619ac0dd85c56f0 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69fcc6b81e248190808695258bce894b completed May 7, 2026, 5:07 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41a7e947b081908757acfb80fa3bc4 completed June 28, 2026, 11:02 p.m.
NEDg Description generation batch_6a41aba1bba08190abafcf9eec135d6b completed June 28, 2026, 11:17 p.m.
NED2 Entity disambiguation (via description) batch_6a41ac93532c8190970eb861195451b9 completed June 28, 2026, 11:21 p.m.
Created at: May 3, 2026, 4:30 p.m.