Triple

T872438
Position Surface form Disambiguated ID Type / Status
Subject Isabel Allende E18842 entity
Predicate notableWork P4 FINISHED
Object Violeta
Violeta is a novel by Chilean author Isabel Allende that follows the tumultuous, century-long life of a woman born during the 1918 Spanish flu pandemic.
 E103169 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: Violeta | Statement: [Isabel Allende, notableWork, Violeta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Violeta
Context triple: [Isabel Allende, notableWork, Violeta]
  • A. Violet
    Violet is a small, typically purple-flowered plant commonly found in temperate regions and widely recognized as a symbol of modesty and springtime.
  • B. Rosa
    Rosa is a genus of flowering plants known for its ornamental roses, prized worldwide for their beauty, fragrance, and cultural symbolism.
  • C. Mariquita
    Mariquita is a historic town in central Colombia known as an early colonial settlement and former mining center.
  • D. Blume
    Blume is the family name of acclaimed English actress Claire Bloom, known for her work in film, television, and theatre.
  • E. Doña Sol
    Doña Sol is a seductive and aristocratic woman who becomes the torero’s dangerous love interest in the 1922 silent film "Blood and Sand."
  • 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: Violeta
Triple: [Isabel Allende, notableWork, Violeta]
Generated description
Violeta is a novel by Chilean author Isabel Allende that follows the tumultuous, century-long life of a woman born during the 1918 Spanish flu pandemic.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Violeta
Target entity description: Violeta is a novel by Chilean author Isabel Allende that follows the tumultuous, century-long life of a woman born during the 1918 Spanish flu pandemic.
  • A. Violet
    Violet is a small, typically purple-flowered plant commonly found in temperate regions and widely recognized as a symbol of modesty and springtime.
  • B. Rosa
    Rosa is a genus of flowering plants known for its ornamental roses, prized worldwide for their beauty, fragrance, and cultural symbolism.
  • C. Mariquita
    Mariquita is a historic town in central Colombia known as an early colonial settlement and former mining center.
  • D. Blume
    Blume is the family name of acclaimed English actress Claire Bloom, known for her work in film, television, and theatre.
  • E. Doña Sol
    Doña Sol is a seductive and aristocratic woman who becomes the torero’s dangerous love interest in the 1922 silent film "Blood and Sand."
  • 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_69a4938db1f081909bcd1ad2713b6096 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4ac96850881908a2d776685126137 completed March 1, 2026, 9:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7b84fb2d0819084c256023bc23dc5 completed March 4, 2026, 4:42 a.m.
NEDg Description generation batch_69a7b985298c8190b465ce0589cd2c24 completed March 4, 2026, 4:48 a.m.
NED2 Entity disambiguation (via description) batch_69a7ba44b79c8190b0ce8a430fe928e5 completed March 4, 2026, 4:51 a.m.
Created at: March 1, 2026, 7:39 p.m.