Triple

T10256763
Position Surface form Disambiguated ID Type / Status
Subject Grégoire Lyonnet E240489 entity
Predicate familyName P18 FINISHED
Object Lyonnet
Lyonnet is a French surname most notably associated with professional dancer Grégoire Lyonnet.
 E854093 NE FINISHED

How this triple was built (4 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: Lyonnet | Statement: [Grégoire Lyonnet, familyName, Lyonnet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lyonnet
Context triple: [Grégoire Lyonnet, familyName, Lyonnet]
  • A. Lyonnais
    Lyonnais is a historical region in east-central France centered around the city of Lyon, known for its rich cultural heritage, gastronomy, and role as a major economic hub.
  • B. Bonaly
    Bonaly is the surname of French figure skater Surya Bonaly, renowned for her powerful athleticism and signature backflip on ice.
  • C. Lugrin
    Lugrin is a commune in eastern France on the southern shore of Lake Geneva, known historically as one of the sites where the Évian Accords negotiations took place.
  • D. Marloie
    Marloie is a village in the Walloon region of Belgium known for its railway station on the Brussels–Luxembourg line.
  • E. Courcier
    Courcier was a French publishing house known for issuing important mathematical and scientific works in the early 19th century.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Lyonnet
Triple: [Grégoire Lyonnet, familyName, Lyonnet]
Generated description
Lyonnet is a French surname most notably associated with professional dancer Grégoire Lyonnet.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lyonnet
Target entity description: Lyonnet is a French surname most notably associated with professional dancer Grégoire Lyonnet.
  • A. Lyonnais
    Lyonnais is a historical region in east-central France centered around the city of Lyon, known for its rich cultural heritage, gastronomy, and role as a major economic hub.
  • B. Bonaly
    Bonaly is the surname of French figure skater Surya Bonaly, renowned for her powerful athleticism and signature backflip on ice.
  • C. Lugrin
    Lugrin is a commune in eastern France on the southern shore of Lake Geneva, known historically as one of the sites where the Évian Accords negotiations took place.
  • D. Marloie
    Marloie is a village in the Walloon region of Belgium known for its railway station on the Brussels–Luxembourg line.
  • E. Courcier
    Courcier was a French publishing house known for issuing important mathematical and scientific works in the early 19th century.
  • F. None of above. chosen

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_69d381a7e198819090280d5ab885d59e completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d24d299881909615872e2777bdea completed April 7, 2026, 9:45 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f7e153b0819084708b6f7127cdea completed April 9, 2026, 12:50 a.m.
NEDg Description generation batch_69d6fcab0bfc8190b47bc165ef3eb15d completed April 9, 2026, 1:11 a.m.
NED2 Entity disambiguation (via description) batch_69d70fc3b15081908d1b67a7094c6210 completed April 9, 2026, 2:32 a.m.
Created at: April 6, 2026, 11:31 a.m.