Triple

T7294366
Position Surface form Disambiguated ID Type / Status
Subject Nathaniel Lyon E164480 entity
Predicate familyName P18 FINISHED
Object Lyon
Lyon is a major city in east-central France known for its historical and architectural landmarks and its renowned culinary tradition.
 E15889 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: Lyon | Statement: [Nathaniel Lyon, familyName, Lyon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lyon
Context triple: [Nathaniel Lyon, familyName, Lyon]
  • A. Lyon
    Lyon is a major city in east-central France known for its historical and architectural landmarks, gastronomy, and role as a key economic and cultural center.
  • B. Lyons
    Lyons is a small city in southeastern Georgia, United States, known as the administrative and commercial hub of Toombs County.
  • C. Lyons
    Lyons is a sports team or athletic program associated with Wheaton College, commonly referred to by this shortened name.
  • D. Clermont-Ferrand
    Clermont-Ferrand is a central French city known for its historic cathedral built of black volcanic stone and as the longtime headquarters of the tire company Michelin.
  • E. Rodez
    Rodez is a historic cathedral city in southern France that serves as the capital of the Aveyron department in the Occitanie region.
  • 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: Lyon
Triple: [Nathaniel Lyon, familyName, Lyon]
Generated description
Lyon is a major city in east-central France known for its historical and architectural landmarks and its renowned culinary tradition.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lyon
Target entity description: Lyon is a major city in east-central France known for its historical and architectural landmarks and its renowned culinary tradition.
  • A. Lyon chosen
    Lyon is a major city in east-central France known for its historical and architectural landmarks, gastronomy, and role as a key economic and cultural center.
  • B. Lyons
    Lyons is a small city in southeastern Georgia, United States, known as the administrative and commercial hub of Toombs County.
  • C. Lyons
    Lyons is a sports team or athletic program associated with Wheaton College, commonly referred to by this shortened name.
  • D. Clermont-Ferrand
    Clermont-Ferrand is a central French city known for its historic cathedral built of black volcanic stone and as the longtime headquarters of the tire company Michelin.
  • E. Rodez
    Rodez is a historic cathedral city in southern France that serves as the capital of the Aveyron department in the Occitanie region.
  • F. None of above.

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_69c6887a499881909dd23341399c59d8 completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6eb8b7cc08190983739bf667057c9 completed March 27, 2026, 8:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7e4e76cf881909e45c3652a372a70 completed March 28, 2026, 2:25 p.m.
NEDg Description generation batch_69c7e6671e2c8190aed42aa673540efa completed March 28, 2026, 2:32 p.m.
NED2 Entity disambiguation (via description) batch_69c7e6cd820881909ef8fd3bc28d2716 completed March 28, 2026, 2:33 p.m.
Created at: March 27, 2026, 3 p.m.