Triple

T8626206
Position Surface form Disambiguated ID Type / Status
Subject Notre musique E204285 entity
Predicate castMember P1668 FINISHED
Object Nade Dieu
Nade Dieu is an actress known for her role in the film "Notre musique" directed by Jean-Luc Godard.
 E747605 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: Nade Dieu | Statement: [Notre musique, castMember, Nade Dieu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nade Dieu
Context triple: [Notre musique, castMember, Nade Dieu]
  • A. Ditat Deus
    Ditat Deus is the Latin state motto of Arizona, meaning "God enriches" or "God gives wealth."
  • B. La Bonne Chanson
    La Bonne Chanson is a celebrated collection of love poems by French Symbolist poet Paul Verlaine, noted for its musicality and emotional intensity.
  • C. La Vie
    La Vie is a 1903 Blue Period painting by Pablo Picasso that portrays a somber, symbolic scene reflecting themes of poverty, despair, and existential struggle.
  • D. Le Très-Haut
    Le Très-Haut is a philosophical novel by Maurice Blanchot that explores themes of power, transcendence, and the limits of human experience through an enigmatic, introspective narrative.
  • E. L’Œuvre
    L’Œuvre is a naturalist novel by Émile Zola that portrays the struggles of an ambitious painter in Paris whose obsessive pursuit of artistic perfection leads to personal and professional ruin.
  • 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: Nade Dieu
Triple: [Notre musique, castMember, Nade Dieu]
Generated description
Nade Dieu is an actress known for her role in the film "Notre musique" directed by Jean-Luc Godard.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nade Dieu
Target entity description: Nade Dieu is an actress known for her role in the film "Notre musique" directed by Jean-Luc Godard.
  • A. Ditat Deus
    Ditat Deus is the Latin state motto of Arizona, meaning "God enriches" or "God gives wealth."
  • B. La Bonne Chanson
    La Bonne Chanson is a celebrated collection of love poems by French Symbolist poet Paul Verlaine, noted for its musicality and emotional intensity.
  • C. La Vie
    La Vie is a 1903 Blue Period painting by Pablo Picasso that portrays a somber, symbolic scene reflecting themes of poverty, despair, and existential struggle.
  • D. Le Très-Haut
    Le Très-Haut is a philosophical novel by Maurice Blanchot that explores themes of power, transcendence, and the limits of human experience through an enigmatic, introspective narrative.
  • E. L’Œuvre
    L’Œuvre is a naturalist novel by Émile Zola that portrays the struggles of an ambitious painter in Paris whose obsessive pursuit of artistic perfection leads to personal and professional ruin.
  • 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_69ca834a4ea0819094970dceb9e389f3 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc472b8fa481909f52f83ea210483e completed March 31, 2026, 10:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69cebbf03c688190a989f16675f6e8a6 completed April 2, 2026, 6:56 p.m.
NEDg Description generation batch_69cebdd3ae908190bc4108b766585cbc completed April 2, 2026, 7:04 p.m.
NED2 Entity disambiguation (via description) batch_69cebf1825008190a97cd2df10f8e406 completed April 2, 2026, 7:10 p.m.
Created at: March 30, 2026, 6:26 p.m.