Triple

T33256333
Position Surface form Disambiguated ID Type / Status
Subject state awards of Kazakhstan E851385 entity
Predicate includes P1393 FINISHED
Object Order of Kurmet
The Order of Kurmet is a Kazakh state honor awarded to individuals for significant contributions to the nation’s economic, social, scientific, or cultural development.
E2043831 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: Order of Kurmet | Statement: [state awards of Kazakhstan, includes, Order of Kurmet]
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: Order of Kurmet
Triple: [state awards of Kazakhstan, includes, Order of Kurmet]
Generated description
The Order of Kurmet is a Kazakh state honor awarded to individuals for significant contributions to the nation’s economic, social, scientific, or cultural development.

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_69f34963135c819084e7f1d483421f00 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6de0ee2308190a9fa3e8b54490e29 completed May 3, 2026, 5:33 a.m.
NED1 Entity disambiguation (via context triple) batch_6a35391641b08190b9fca62aa8731458 completed June 19, 2026, 12:41 p.m.
NEDg Description generation batch_6a353a0b12948190aeaf63ebc1bcf2b3 completed June 19, 2026, 12:46 p.m.
NED2 Entity disambiguation (via description) batch_6a353a7e57a481908e6cd908e633f878 completed June 19, 2026, 12:47 p.m.
Created at: May 1, 2026, 1:31 a.m.