Triple

T94540
Position Surface form Disambiguated ID Type / Status
Subject Guido van Rossum E1899 entity
Predicate spouse P13 FINISHED
Object Kim Knapp
Kim Knapp is known as the spouse of Guido van Rossum, the creator of the Python programming language.
E55827 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: Kim Knapp | Statement: [Guido van Rossum, spouse, Kim Knapp]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kim Knapp
Context triple: [Guido van Rossum, spouse, Kim Knapp]
  • A. Katherine Rogers
    Katherine Rogers was the mother of John Harvard, the English clergyman whose bequest helped found Harvard College in colonial Massachusetts.
  • B. Lisa Rogers
    Lisa Rogers is a member of the Rogers family, known as the daughter of Canadian businessman and media magnate Ted Rogers.
  • C. Joyce King
    Joyce King is a personal name shared by multiple individuals, including professionals in fields such as academia, law, and the arts.
  • D. Melinda Rogers
    Melinda Rogers is a Canadian business executive and member of the Rogers family, known for her leadership roles within Rogers Communications.
  • E. Alicia Nash
    Alicia Nash was a Salvadoran-American physicist and mental health advocate best known as the devoted wife of mathematician John Nash, whose life with him was portrayed in the film "A Beautiful Mind."
  • 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: Kim Knapp
Triple: [Guido van Rossum, spouse, Kim Knapp]
Generated description
Kim Knapp is known as the spouse of Guido van Rossum, the creator of the Python programming language.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kim Knapp
Target entity description: Kim Knapp is known as the spouse of Guido van Rossum, the creator of the Python programming language.
  • A. Katherine Rogers
    Katherine Rogers was the mother of John Harvard, the English clergyman whose bequest helped found Harvard College in colonial Massachusetts.
  • B. Lisa Rogers
    Lisa Rogers is a member of the Rogers family, known as the daughter of Canadian businessman and media magnate Ted Rogers.
  • C. Joyce King
    Joyce King is a personal name shared by multiple individuals, including professionals in fields such as academia, law, and the arts.
  • D. Melinda Rogers
    Melinda Rogers is a Canadian business executive and member of the Rogers family, known for her leadership roles within Rogers Communications.
  • E. Alicia Nash
    Alicia Nash was a Salvadoran-American physicist and mental health advocate best known as the devoted wife of mathematician John Nash, whose life with him was portrayed in the film "A Beautiful Mind."
  • 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_69a24d4862f881908cc8b89d3a78031d completed Feb. 28, 2026, 2:04 a.m.
NER Named-entity recognition batch_69a24fd4777c81909ea9b9a6bd4f7ad5 completed Feb. 28, 2026, 2:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69a43e6744888190b4514f057fc98498 completed March 1, 2026, 1:25 p.m.
NEDg Description generation batch_69a43ffa92e88190a40155190dbf8b9c completed March 1, 2026, 1:32 p.m.
NED2 Entity disambiguation (via description) batch_69a44046b4cc819085012cce79176fc6 completed March 1, 2026, 1:33 p.m.
Created at: Feb. 28, 2026, 2:09 a.m.