Triple

T12436207
Position Surface form Disambiguated ID Type / Status
Subject Harlem Désir E297149 entity
Predicate familyName P18 FINISHED
Object Désir
Désir is a French surname borne by various notable individuals, including politicians and public figures.
E983682 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: Désir | Statement: [Harlem Désir, familyName, Désir]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Désir
Context triple: [Harlem Désir, familyName, Désir]
  • A. Le Plaisir
    Le Plaisir is a 1952 French anthology film directed by Max Ophüls, adapting three Guy de Maupassant stories into elegant, interwoven tales of love, desire, and human folly.
  • B. Plaisir d’amour
    "Plaisir d’amour" is a classic 18th-century French love song, widely known through numerous interpretations including a popular rendition by Nana Mouskouri.
  • C. L'Amant
    L'Amant is a semi-autobiographical novel by Marguerite Duras that recounts a passionate adolescent love affair in colonial French Indochina.
  • D. De l'amour
    De l'amour is a psychological and philosophical treatise by Stendhal that analyzes the nature, stages, and illusions of romantic love.
  • E. Folle Blanche
    Folle Blanche is a traditional French white grape variety historically prized in Armagnac and Cognac production for its high acidity and delicate, floral spirits.
  • 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: Désir
Triple: [Harlem Désir, familyName, Désir]
Generated description
Désir is a French surname borne by various notable individuals, including politicians and public figures.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Désir
Target entity description: Désir is a French surname borne by various notable individuals, including politicians and public figures.
  • A. Le Plaisir
    Le Plaisir is a 1952 French anthology film directed by Max Ophüls, adapting three Guy de Maupassant stories into elegant, interwoven tales of love, desire, and human folly.
  • B. Plaisir d’amour
    "Plaisir d’amour" is a classic 18th-century French love song, widely known through numerous interpretations including a popular rendition by Nana Mouskouri.
  • C. L'Amant
    L'Amant is a semi-autobiographical novel by Marguerite Duras that recounts a passionate adolescent love affair in colonial French Indochina.
  • D. De l'amour
    De l'amour is a psychological and philosophical treatise by Stendhal that analyzes the nature, stages, and illusions of romantic love.
  • E. Folle Blanche
    Folle Blanche is a traditional French white grape variety historically prized in Armagnac and Cognac production for its high acidity and delicate, floral spirits.
  • 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_69d6ada0640c81908c061d7fb3d47786 completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d94d8c8fd481909b35ac504127a1b6 completed April 10, 2026, 7:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63f06d16481909ed2eb5195ebd7e4 completed May 2, 2026, 6:14 p.m.
NEDg Description generation batch_69f6400fe9888190ae8244ccc8e8bc39 completed May 2, 2026, 6:18 p.m.
NED2 Entity disambiguation (via description) batch_69f64168d23881908daee7d7cba2160d completed May 2, 2026, 6:24 p.m.
Created at: April 8, 2026, 9:55 p.m.