Triple

T19858545
Position Surface form Disambiguated ID Type / Status
Subject Quino E477198 entity
Predicate notableWork P4 FINISHED
Object Mafalda
Mafalda is an iconic Argentine comic strip character—a sharp, socially conscious little girl—created by cartoonist Quino, known for her humorous yet critical reflections on politics and society.
 E1398170 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: Mafalda | Statement: [Quino, notableWork, Mafalda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mafalda
Context triple: [Quino, notableWork, Mafalda]
  • A. Mafalda
    Mafalda is a princess of the House of Savoy, best known as the daughter of King Victor Emmanuel III of Italy and for her tragic death in a Nazi concentration camp during World War II.
  • B. Eliana
    Eliana is a feminine given name of Hebrew and Latin origin, often interpreted to mean "God has answered" or "my God has answered."
  • C. Marlen
    Marlen is a village district of the town of Kehl in the German state of Baden-Württemberg.
  • D. Marcela
    Marcela is one of the given names of Alexia Juliana Marcela Laurentien, a member of the Dutch royal family.
  • E. Rafaela
    Rafaela is a major city in central Argentina known for its agricultural industry and role as a regional economic center.
  • 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: Mafalda
Triple: [Quino, notableWork, Mafalda]
Generated description
Mafalda is an iconic Argentine comic strip character—a sharp, socially conscious little girl—created by cartoonist Quino, known for her humorous yet critical reflections on politics and society.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mafalda
Target entity description: Mafalda is an iconic Argentine comic strip character—a sharp, socially conscious little girl—created by cartoonist Quino, known for her humorous yet critical reflections on politics and society.
  • A. Mafalda
    Mafalda is a princess of the House of Savoy, best known as the daughter of King Victor Emmanuel III of Italy and for her tragic death in a Nazi concentration camp during World War II.
  • B. Eliana
    Eliana is a feminine given name of Hebrew and Latin origin, often interpreted to mean "God has answered" or "my God has answered."
  • C. Marlen
    Marlen is a village district of the town of Kehl in the German state of Baden-Württemberg.
  • D. Marcela
    Marcela is one of the given names of Alexia Juliana Marcela Laurentien, a member of the Dutch royal family.
  • E. Rafaela
    Rafaela is a major city in central Argentina known for its agricultural industry and role as a regional economic center.
  • 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_69d8e51e7d948190aedbcd6c30361c39 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e6586dbbf0819089e7157d416aeaaf completed April 20, 2026, 4:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a07d445b4c481908a444d5047b3e403 completed May 16, 2026, 2:19 a.m.
NEDg Description generation batch_6a07d50359f08190bafa8865168ee0b4 completed May 16, 2026, 2:22 a.m.
NED2 Entity disambiguation (via description) batch_6a07d5d7c4bc8190ab189fa556a956d7 completed May 16, 2026, 2:26 a.m.
Created at: April 10, 2026, 1:51 p.m.