Triple

T25851576
Position Surface form Disambiguated ID Type / Status
Subject 1977 FIFA World Youth Championship E651223 entity
Predicate bestPlayer P2630 FINISHED
Object Vladimir Bessonov
Vladimir Bessonov is a former Soviet footballer renowned as a versatile defender and midfielder who starred for Dynamo Kyiv and the USSR national team.
E2293087 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: Vladimir Bessonov | Statement: [1977 FIFA World Youth Championship, bestPlayer, Vladimir Bessonov]
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: Vladimir Bessonov
Triple: [1977 FIFA World Youth Championship, bestPlayer, Vladimir Bessonov]
Generated description
Vladimir Bessonov is a former Soviet footballer renowned as a versatile defender and midfielder who starred for Dynamo Kyiv and the USSR national team.

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_69e7ab39035c8190be15c8aaee1bb858 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f6023b96208190925872085ada10e3 completed May 2, 2026, 1:55 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7a65d0c1b88190bd1e3f7b0eaf4c5c completed Aug. 10, 2026, 11:59 p.m.
NEDg Description generation batch_6a7a661ca6648190ade6baf8776ec857 completed Aug. 11, 2026, midnight
NED2 Entity disambiguation (via description) batch_6a7a6672d3848190b78360d61999b9e3 completed Aug. 11, 2026, 12:01 a.m.
Created at: April 22, 2026, 7:58 a.m.