Triple

T1525645
Position Surface form Disambiguated ID Type / Status
Subject Veronika Decides to Die E32329 entity
Predicate mainCharacter P1183 FINISHED
Object Veronika
Veronika is the troubled young protagonist of Paulo Coelho's novel "Veronika Decides to Die," whose suicide attempt leads her to a transformative stay in a mental institution.
 E174317 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: Veronika | Statement: [Veronika Decides to Die, mainCharacter, Veronika]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Veronika
Context triple: [Veronika Decides to Die, mainCharacter, Veronika]
  • A. Vera
    Vera Rubin was an influential American astronomer whose pioneering work on galaxy rotation curves provided key evidence for the existence of dark matter.
  • B. Milena
    Milena is the birth name of actress Mila Kunis, a Ukrainian-born American performer known for roles in "That '70s Show" and "Black Swan."
  • C. Valeria
    Valeria was a Roman imperial princess and later empress, best known as the daughter of Emperor Diocletian and for her tragic fate during the political turmoil of the Tetrarchy.
  • D. Valeria
    Valeria is the clever, sharp-tongued heroine of George Farquhar’s Restoration comedy "The Witty Fair One."
  • E. Verena
    Verena is a feminine given name of Latin origin, commonly used in German-speaking and other European countries.
  • 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: Veronika
Triple: [Veronika Decides to Die, mainCharacter, Veronika]
Generated description
Veronika is the troubled young protagonist of Paulo Coelho's novel "Veronika Decides to Die," whose suicide attempt leads her to a transformative stay in a mental institution.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Veronika
Target entity description: Veronika is the troubled young protagonist of Paulo Coelho's novel "Veronika Decides to Die," whose suicide attempt leads her to a transformative stay in a mental institution.
  • A. Vera
    Vera Rubin was an influential American astronomer whose pioneering work on galaxy rotation curves provided key evidence for the existence of dark matter.
  • B. Milena
    Milena is the birth name of actress Mila Kunis, a Ukrainian-born American performer known for roles in "That '70s Show" and "Black Swan."
  • C. Valeria
    Valeria was a Roman imperial princess and later empress, best known as the daughter of Emperor Diocletian and for her tragic fate during the political turmoil of the Tetrarchy.
  • D. Valeria
    Valeria is the clever, sharp-tongued heroine of George Farquhar’s Restoration comedy "The Witty Fair One."
  • E. Verena
    Verena is a feminine given name of Latin origin, commonly used in German-speaking and other European countries.
  • 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_69a885e9b0ac819093a9806ad0efc82c completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69aa61f7bb60819094774ecc632255de completed March 6, 2026, 5:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad2953c5308190984d20f62b7303fd completed March 8, 2026, 7:46 a.m.
NEDg Description generation batch_69ad2a1742d48190a82c1fc8c81d5c21 completed March 8, 2026, 7:49 a.m.
NED2 Entity disambiguation (via description) batch_69ad2aa092b08190930f1c39d963861b completed March 8, 2026, 7:52 a.m.
Created at: March 4, 2026, 7:26 p.m.