Triple

T11493991
Position Surface form Disambiguated ID Type / Status
Subject Olive E272486 entity
Predicate hasVariant P455 FINISHED
Object Olivette
Olivette is a diminutive given name derived from Olive, often associated with peace and nature.
 E929694 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: Olivette | Statement: [Olive, hasVariant, Olivette]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Olivette
Context triple: [Olive, hasVariant, Olivette]
  • A. Delphine
    Delphine is an epistolary novel by Madame de Staël that explores themes of love, social convention, and women's independence in late 18th-century French society.
  • B. Margeride
    Margeride is a mountainous and sparsely populated region in south-central France known for its granite plateaus, forests, and traditional rural landscapes.
  • C. Marzelline
    Marzelline is a character in Beethoven's opera "Fidelio," portrayed as the jailer Rocco’s daughter who becomes romantically entangled with the disguised heroine.
  • D. Béline
    Béline is the hypocritical and scheming second wife of Argan in Molière’s comedy "Le Malade imaginaire."
  • E. Capucine
    Capucine was a French fashion model and film actress best known for her elegant screen presence in 1960s comedies and dramas, including roles in films like The Pink Panther.
  • 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: Olivette
Triple: [Olive, hasVariant, Olivette]
Generated description
Olivette is a diminutive given name derived from Olive, often associated with peace and nature.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Olivette
Target entity description: Olivette is a diminutive given name derived from Olive, often associated with peace and nature.
  • A. Delphine
    Delphine is an epistolary novel by Madame de Staël that explores themes of love, social convention, and women's independence in late 18th-century French society.
  • B. Margeride
    Margeride is a mountainous and sparsely populated region in south-central France known for its granite plateaus, forests, and traditional rural landscapes.
  • C. Marzelline
    Marzelline is a character in Beethoven's opera "Fidelio," portrayed as the jailer Rocco’s daughter who becomes romantically entangled with the disguised heroine.
  • D. Béline
    Béline is the hypocritical and scheming second wife of Argan in Molière’s comedy "Le Malade imaginaire."
  • E. Capucine
    Capucine was a French fashion model and film actress best known for her elegant screen presence in 1960s comedies and dramas, including roles in films like The Pink Panther.
  • 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_69d6aae1b09881909ce2ded3fa0c14fa completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d85ddffdf88190a00e94ad5b8b91a5 completed April 10, 2026, 2:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69e624c3691081908f2e448aebab40aa completed April 20, 2026, 1:06 p.m.
NEDg Description generation batch_69e62cf224f881908badcdab6aea1aef completed April 20, 2026, 1:41 p.m.
NED2 Entity disambiguation (via description) batch_69e663ffedfc8190a2b51995c62d1e6b completed April 20, 2026, 5:36 p.m.
Created at: April 8, 2026, 9:36 p.m.