Triple

T7725457
Position Surface form Disambiguated ID Type / Status
Subject Robert Lepage E175117 entity
Predicate familyName P18 FINISHED
Object Lepage
Lepage is a French-origin surname borne by various notable individuals, including artists, politicians, and athletes, particularly in Canada and France.
 E684715 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: Lepage | Statement: [Robert Lepage, familyName, Lepage]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lepage
Context triple: [Robert Lepage, familyName, Lepage]
  • A. Ganthier
    Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
  • B. Lebrun
    Lebrun is a French surname borne by various notable figures in politics, arts, and other fields.
  • C. Choulex
    Choulex is a small municipality in the canton of Geneva in southwestern Switzerland, known for its rural character and proximity to the city of Geneva.
  • D. Breuillet
    Breuillet is a commune in the Essonne department in the Île-de-France region of northern France.
  • 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: Lepage
Triple: [Robert Lepage, familyName, Lepage]
Generated description
Lepage is a French-origin surname borne by various notable individuals, including artists, politicians, and athletes, particularly in Canada and France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lepage
Target entity description: Lepage is a French-origin surname borne by various notable individuals, including artists, politicians, and athletes, particularly in Canada and France.
  • A. Ganthier
    Ganthier is a commune in western Haiti known for its rural character and proximity to the capital, Port-au-Prince.
  • B. Lebrun
    Lebrun is a French surname borne by various notable figures in politics, arts, and other fields.
  • C. Choulex
    Choulex is a small municipality in the canton of Geneva in southwestern Switzerland, known for its rural character and proximity to the city of Geneva.
  • D. Breuillet
    Breuillet is a commune in the Essonne department in the Île-de-France region of northern France.
  • 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_69c6995d541c81909eaa646b1a8369a9 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7031394e48190833b906af9166fe5 completed March 27, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8b523aeb481909d132509b56b5602 completed March 29, 2026, 5:14 a.m.
NEDg Description generation batch_69c8b5ae7e98819098f0f54dd95f8c9e completed March 29, 2026, 5:16 a.m.
NED2 Entity disambiguation (via description) batch_69c8b63c93b48190bab5314723ed4c24 completed March 29, 2026, 5:18 a.m.
Created at: March 27, 2026, 4:05 p.m.