Triple

T13276744
Position Surface form Disambiguated ID Type / Status
Subject Le Soupirant E316209 entity
Predicate starredActor P5563 FINISHED
Object France Arnell
France Arnell is an actress best known for her role in the French film "Le Soupirant."
E1031777 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: France Arnell | Statement: [Le Soupirant, starredActor, France Arnell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: France Arnell
Context triple: [Le Soupirant, starredActor, France Arnell]
  • A. France Bélisle
    France Bélisle is a Canadian politician who serves as the mayor of Gatineau, Quebec.
  • B. Dominique La Rue
    Dominique La Rue is a seductive and cunning nightclub singer and con artist in the 1989 crime-comedy film "Harlem Nights."
  • C. Germaine Aussey
    Germaine Aussey was a French film actress active in the 1930s and 1940s, known for her roles in comedies and popular European cinema of the era.
  • D. Jean Fayle
    Jean Fayle is a person after whom another individual or entity named Jean was named, suggesting they were an influential or significant namesake.
  • E. Jean Renaudie
    Jean Renaudie was a French architect known for his radical, geometric social housing projects and influential role in postwar modernist architecture.
  • 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: France Arnell
Triple: [Le Soupirant, starredActor, France Arnell]
Generated description
France Arnell is an actress best known for her role in the French film "Le Soupirant."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: France Arnell
Target entity description: France Arnell is an actress best known for her role in the French film "Le Soupirant."
  • A. France Bélisle
    France Bélisle is a Canadian politician who serves as the mayor of Gatineau, Quebec.
  • B. Dominique La Rue
    Dominique La Rue is a seductive and cunning nightclub singer and con artist in the 1989 crime-comedy film "Harlem Nights."
  • C. Germaine Aussey
    Germaine Aussey was a French film actress active in the 1930s and 1940s, known for her roles in comedies and popular European cinema of the era.
  • D. Jean Fayle
    Jean Fayle is a person after whom another individual or entity named Jean was named, suggesting they were an influential or significant namesake.
  • E. Jean Renaudie
    Jean Renaudie was a French architect known for his radical, geometric social housing projects and influential role in postwar modernist architecture.
  • 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_69d806b349908190a9a61dd9323bf153 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99042f56c819082440c89c0adc442 completed April 11, 2026, 12:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69f70a54ff488190a759b46963c0d842 completed May 3, 2026, 8:41 a.m.
NEDg Description generation batch_69f713088cc48190b705336339527f46 completed May 3, 2026, 9:19 a.m.
NED2 Entity disambiguation (via description) batch_69f713bd94048190a61dbd955bd1c542 completed May 3, 2026, 9:22 a.m.
Created at: April 9, 2026, 9:26 p.m.