Triple

T27421934
Position Surface form Disambiguated ID Type / Status
Subject Harari regional administration E693067 entity
Predicate hasLegislativeBody P239 FINISHED
Object Harari Regional Council
The Harari Regional Council is the legislative body governing Ethiopia’s Harari Regional State, responsible for making regional laws and overseeing local administration.
E693067 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: Harari Regional Council | Statement: [Harari regional administration, hasLegislativeBody, Harari Regional 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: Harari Regional Council
Triple: [Harari regional administration, hasLegislativeBody, Harari Regional Council]
Generated description
The Harari Regional Council is the legislative body governing Ethiopia’s Harari Regional State, responsible for making regional laws and overseeing local administration.

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_69ef5208617081908f731d312e0fd1bc completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62d1dcfa8819080a8b0dd701d69af completed May 2, 2026, 4:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12b2483f30819098bf33b785f64295 completed May 24, 2026, 8:09 a.m.
NEDg Description generation batch_6a12b41d20008190a453cd775e7f8240 completed May 24, 2026, 8:17 a.m.
NED2 Entity disambiguation (via description) batch_6a12b4da86248190ae6ff993c5b904df completed May 24, 2026, 8:20 a.m.
Created at: April 27, 2026, 12:36 p.m.