Triple

T2723360
Position Surface form Disambiguated ID Type / Status
Subject La Maja Vestida E60131 entity
Predicate possibleModel P41880 FINISHED
Object Pepita Tudó
Pepita Tudó was a Spanish woman best known as the mistress of Manuel de Godoy and a likely muse for Francisco Goya, possibly inspiring his famous painting "La Maja Vestida."
E292297 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: Pepita Tudó | Statement: [La Maja Vestida, possibleModel, Pepita Tudó]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pepita Tudó
Context triple: [La Maja Vestida, possibleModel, Pepita Tudó]
  • A. Ilona Komocsin
    Ilona Komocsin was the wife and muse of Hungarian architect and sculptor Jenő Bory, for whom he built the romantic Bory Castle as a monument to their love.
  • B. Katalin
    Katalin is a Hungarian given name most prominently associated with biochemist Katalin Karikó, a pioneer of mRNA technology used in COVID-19 vaccines.
  • C. Ilona Kovács
    Ilona Kovács was the wife of renowned Hungarian-American film director Michael Curtiz.
  • D. Pepita Embil
    Pepita Embil was a renowned Spanish zarzuela and opera singer of the mid-20th century and the mother of tenor Plácido Domingo.
  • E. Ruzena Bajcsy
    Ruzena Bajcsy is a pioneering computer scientist and engineer known for her influential work in robotics, computer vision, and artificial intelligence.
  • 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: Pepita Tudó
Triple: [La Maja Vestida, possibleModel, Pepita Tudó]
Generated description
Pepita Tudó was a Spanish woman best known as the mistress of Manuel de Godoy and a likely muse for Francisco Goya, possibly inspiring his famous painting "La Maja Vestida."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Pepita Tudó
Target entity description: Pepita Tudó was a Spanish woman best known as the mistress of Manuel de Godoy and a likely muse for Francisco Goya, possibly inspiring his famous painting "La Maja Vestida."
  • A. Ilona Komocsin
    Ilona Komocsin was the wife and muse of Hungarian architect and sculptor Jenő Bory, for whom he built the romantic Bory Castle as a monument to their love.
  • B. Katalin
    Katalin is a Hungarian given name most prominently associated with biochemist Katalin Karikó, a pioneer of mRNA technology used in COVID-19 vaccines.
  • C. Ilona Kovács
    Ilona Kovács was the wife of renowned Hungarian-American film director Michael Curtiz.
  • D. Pepita Embil
    Pepita Embil was a renowned Spanish zarzuela and opera singer of the mid-20th century and the mother of tenor Plácido Domingo.
  • E. Ruzena Bajcsy
    Ruzena Bajcsy is a pioneering computer scientist and engineer known for her influential work in robotics, computer vision, and artificial intelligence.
  • 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_69ab4b746d248190958e052045c09255 completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdd1fc30c81909ac06588d50abdf8 completed March 7, 2026, 8:09 a.m.
NED1 Entity disambiguation (via context triple) batch_69afb6939a50819087ac2c55337ceae3 completed March 10, 2026, 6:13 a.m.
NEDg Description generation batch_69afb74d9f4c8190b6b3f568babfb7b5 completed March 10, 2026, 6:16 a.m.
NED2 Entity disambiguation (via description) batch_69afb7c2b9d08190bce599c364d809b7 completed March 10, 2026, 6:18 a.m.
Created at: March 6, 2026, 9:55 p.m.