Triple

T26327530
Position Surface form Disambiguated ID Type / Status
Subject AS Monaco basketball team E662293 entity
Predicate president P8 FINISHED
Object Sergey Dyadechko
Sergey Dyadechko is a Ukrainian businessman and sports executive best known for leading AS Monaco Basket’s rise into a prominent European basketball club.
E2293503 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: Sergey Dyadechko | Statement: [AS Monaco basketball team, president, Sergey Dyadechko]
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: Sergey Dyadechko
Triple: [AS Monaco basketball team, president, Sergey Dyadechko]
Generated description
Sergey Dyadechko is a Ukrainian businessman and sports executive best known for leading AS Monaco Basket’s rise into a prominent European basketball club.

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_69ee812f32748190871d970c4e2a8ddf completed April 26, 2026, 9:18 p.m.
NER Named-entity recognition batch_69f60f65f9f48190ba299fb3e435e67a completed May 2, 2026, 2:51 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7ab5a1b7c08190a150db6a3b889d79 completed Aug. 11, 2026, 5:39 a.m.
NEDg Description generation batch_6a7ab5f5e69881909d1d2ab55acde589 completed Aug. 11, 2026, 5:41 a.m.
NED2 Entity disambiguation (via description) batch_6a7ab629689081908901ad65a776f819 completed Aug. 11, 2026, 5:42 a.m.
Created at: April 26, 2026, 10:31 p.m.