Triple

T16064560
Position Surface form Disambiguated ID Type / Status
Subject Ubisoft E389699 entity
Predicate foundedBy P104 FINISHED
Object Yves Guillemot
Yves Guillemot is a French businessman best known as the co-founder and long-time CEO of the video game company Ubisoft.
E1619072 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: Yves Guillemot | Statement: [Ubisoft, foundedBy, Yves Guillemot]
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: Yves Guillemot
Triple: [Ubisoft, foundedBy, Yves Guillemot]
Generated description
Yves Guillemot is a French businessman best known as the co-founder and long-time CEO of the video game company Ubisoft.

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_69d86daf32ec8190a8c0466c8f49c3c0 completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e1837b048881908326739bbede756f completed April 17, 2026, 12:48 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f9615833481909761d6de67ce1be0 completed May 21, 2026, 11:32 p.m.
NEDg Description generation batch_6a0f9767ddc081909f9cb49ec15c3ca0 completed May 21, 2026, 11:38 p.m.
NED2 Entity disambiguation (via description) batch_6a0f9c2334688190bae5d6f0f57ef036 completed May 21, 2026, 11:58 p.m.
Created at: April 10, 2026, 4:57 a.m.