Triple

T2605004
Position Surface form Disambiguated ID Type / Status
Subject Charles Dickens E58638 entity
Predicate child P120 FINISHED
Object Kate Perugini
Kate Perugini was a British painter and the daughter of novelist Charles Dickens, known for her portrait work and connections within Victorian artistic circles.
E283925 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: Kate Perugini | Statement: [Charles Dickens, child, Kate Perugini]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kate Perugini
Context triple: [Charles Dickens, child, Kate Perugini]
  • A. Gina Ruberti
    Gina Ruberti was the wife of Bruno Mussolini, the son of Italian dictator Benito Mussolini.
  • B. Thea Almerigotti
    Thea Almerigotti was the wife of Fiorello H. La Guardia, the influential three-term mayor of New York City in the early 20th century.
  • C. Laura Martinozzi
    Laura Martinozzi was an Italian noblewoman and duchess of Modena, a niece of Cardinal Mazarin and a politically influential figure in 17th-century Italy.
  • D. Angelica Galante
    Angelica Galante was the mother of the renowned Italian Baroque sculptor and architect Gian Lorenzo Bernini.
  • E. Tharita Cesaroni
    Tharita Cesaroni is an Italian film producer and cinematographer known for her work behind the camera and for being married to actor Dermot Mulroney.
  • 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: Kate Perugini
Triple: [Charles Dickens, child, Kate Perugini]
Generated description
Kate Perugini was a British painter and the daughter of novelist Charles Dickens, known for her portrait work and connections within Victorian artistic circles.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kate Perugini
Target entity description: Kate Perugini was a British painter and the daughter of novelist Charles Dickens, known for her portrait work and connections within Victorian artistic circles.
  • A. Gina Ruberti
    Gina Ruberti was the wife of Bruno Mussolini, the son of Italian dictator Benito Mussolini.
  • B. Thea Almerigotti
    Thea Almerigotti was the wife of Fiorello H. La Guardia, the influential three-term mayor of New York City in the early 20th century.
  • C. Laura Martinozzi
    Laura Martinozzi was an Italian noblewoman and duchess of Modena, a niece of Cardinal Mazarin and a politically influential figure in 17th-century Italy.
  • D. Angelica Galante
    Angelica Galante was the mother of the renowned Italian Baroque sculptor and architect Gian Lorenzo Bernini.
  • E. Tharita Cesaroni
    Tharita Cesaroni is an Italian film producer and cinematographer known for her work behind the camera and for being married to actor Dermot Mulroney.
  • 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_69ab4ac3523881909679750c9f8c2dec completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd864958c8190b3ad6123f1ac78ca completed March 7, 2026, 7:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69af907ebc348190b1556a2104cba6f1 completed March 10, 2026, 3:31 a.m.
NEDg Description generation batch_69af90f63dac8190b3282b5029d22fab completed March 10, 2026, 3:33 a.m.
NED2 Entity disambiguation (via description) batch_69af918e7b50819082f37f9cdb3271a2 completed March 10, 2026, 3:35 a.m.
Created at: March 6, 2026, 9:49 p.m.